CN113888086B - Article signing method, device, equipment and storage medium based on image recognition - Google Patents
Article signing method, device, equipment and storage medium based on image recognition Download PDFInfo
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Abstract
The invention relates to an artificial intelligence technology, and discloses an article signing method based on image recognition, which comprises the following steps: obtaining monitoring pictures of a preset area at a first moment and a second moment, respectively carrying out area division and corresponding coding on the two monitoring pictures, selecting two areas with corresponding coding one by one, respectively extracting global features and local features of the two areas, calculating difference values of the two areas with corresponding coding according to the extracted global features and local features, further determining that an article in the area is not signed when the difference value is smaller than a difference threshold value, determining that the article in the area is signed when the difference value is larger than or equal to the difference threshold value, and reminding a user. In addition, the invention also relates to a blockchain technology, and the monitoring picture can be stored in a node of the blockchain. The invention also provides an article signing device based on image recognition, electronic equipment and a storage medium. The invention can simplify the process of signing in the articles.
Description
Technical Field
The present invention relates to the field of artificial intelligence technologies, and in particular, to an article signing method and apparatus based on image recognition, an electronic device, and a computer readable storage medium.
Background
With the rapid development of internet economy and logistics industry, people more and more commonly perform online shopping and transport various cargoes by utilizing logistics, so that a great number of logistics objects are required to be signed, when people sign the logistics objects, people often need to perform manual signing or use verification codes and the like to perform identity verification signing, and users are required to actively execute a complicated signing process.
In the existing signing method, the user is required to sign the object manually or actively by using a verification code and the like, and prompt cannot be realized in time after signing, so that the signing process is tedious and user experience is reduced, and therefore, how to simplify the signing process of the object is realized becomes a focus of attention of people.
Disclosure of Invention
The invention provides an article signing method and device based on image recognition and a computer readable storage medium, and mainly aims to solve the problem of long process for signing articles.
In order to achieve the above object, the present invention provides an article signing method based on image recognition, including:
Acquiring a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
Selecting one of the first image areas one by one as a target area, and extracting image features of the target area;
Acquiring a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the second image areas according to a preset encoding mode;
Selecting a region with the same number as the target region from the second image region as a region to be compared, and extracting image features of the region to be compared;
calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared, and judging whether the difference value is larger than a preset difference threshold value or not;
when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed;
And when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
Optionally, the dividing the first screen into a plurality of first image areas according to a preset size includes:
generating an image frame according to the preset size;
And carrying out non-repeated frame selection on the areas in the first picture by utilizing the image frame until all the areas in the first picture are frame-selected, so as to obtain a plurality of first image areas.
In detail, the preset size may be data such as a length and a width of the area stored in each article in the first screen, which are acquired in advance.
Optionally, the encoding the plurality of first image areas according to a preset encoding mode includes:
selecting a column of image areas from the plurality of first image areas one by one in a sequence from top to bottom as a target column;
Each first image region in the target column is incrementally encoded in a left-to-right order.
Optionally, the extracting the image feature of the target area includes:
generating global features of the target region according to pixel gradients in the target region;
Utilizing a preset sliding window to frame and select the regions in the target region one by one to obtain a pixel window;
generating local features of the target area according to pixel values in each pixel window;
and collecting the global features and the local features as image features of the target area.
Optionally, the generating the global feature of the target region according to the pixel gradient in the target region includes:
Counting the pixel value of each pixel point in the target area;
Taking the maximum pixel value and the minimum pixel value in the pixel values as parameters of a preset mapping function, and mapping the pixel value of each pixel point in the target area into a preset range by utilizing the preset mapping function;
and calculating the pixel gradient of each row of pixels in the target area after mapping, converting the pixel gradient of each row of pixels into row vectors, and splicing the row vectors into global features of the target area.
Optionally, the generating the local feature of the target area according to the pixel value in each pixel window includes:
selecting one pixel point from the pixel window one by one as a target pixel point;
judging whether the pixel value of the target pixel point is an extremum in the pixel window;
When the pixel value of the target pixel point is not an extremum in the pixel window, returning to the step of selecting one pixel point from the pixel window one by one as the target pixel point;
when the pixel value of the target pixel point is an extremum in the pixel window, determining the target pixel point as a key point;
And vectorizing pixel values of all key points in all pixel windows, and collecting the obtained vectors as local features of the target area.
Optionally, the calculating a difference value between the image feature of the target region and the image feature of the region to be compared includes:
Calculating a first difference value between the global feature of the target area and the global feature of the area to be compared by using a preset first distance algorithm;
Calculating a second difference value between the local features of the target area and the local features of the area to be compared by using a preset second distance algorithm;
And calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared according to the first difference value and the second difference value by using a preset weight algorithm.
In order to solve the above problems, the present invention further provides an article signing device based on image recognition, the device comprising:
The first image dividing module is used for obtaining a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
the first feature extraction module is used for selecting one of the plurality of first image areas one by one as a target area and extracting image features of the target area;
the second image dividing module is used for obtaining a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the plurality of second image areas according to a preset encoding mode;
The second feature extraction module is used for selecting a region with the same number as the target region from the second image region as a region to be compared and extracting the image features of the region to be compared;
The signing judging module is used for calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared and judging whether the difference value is larger than a preset difference threshold value or not; when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed; and when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the image recognition-based item signing method described above.
In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having stored therein at least one computer program that is executed by a processor in an electronic device to implement the above-mentioned image recognition-based article signing method.
According to the embodiment of the invention, the image of the sequential time point of the area where the article is stored can be subjected to feature extraction, so that whether the article stored in the area where the article is stored is signed by a user or not is judged according to the image features corresponding to the image captured on the sequential time point, and further, the user is directly signed and reminded, confirmation or operation is not needed by the user, the non-sense signing is realized, and the article signing flow is simplified. Therefore, the method, the device, the electronic equipment and the computer readable storage medium for signing articles based on image recognition can solve the problem of long process for signing articles.
Drawings
FIG. 1 is a flowchart of an image recognition-based method for signing in an article according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for generating global features of a target region according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating a method for generating local features of a target region according to an embodiment of the present invention;
FIG. 4 is a functional block diagram of an article signing device based on image recognition according to an embodiment of the present invention;
Fig. 5 is a schematic structural diagram of an electronic device for implementing the article signing method based on image recognition according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides an article signing method based on image recognition. The execution subject of the article signing method based on image recognition includes, but is not limited to, at least one of a server, a terminal and the like capable of being configured to execute the method provided by the embodiment of the application. In other words, the image recognition-based item signing method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flowchart of an article signing method based on image recognition according to an embodiment of the present invention is shown. In this embodiment, the method for signing an article based on image recognition includes:
S1, acquiring a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode.
In the embodiment of the invention, the preset area can be an area for storing logistics articles, such as logistics warehouse, express delivery collection and the like, and the change surface of the preset area captured by a pre-installed camera or video recorder and other equipment with an image capturing function at a first moment can be obtained to be a first picture.
For example, the first picture is grabbed from a data storage area corresponding to a pre-installed device with an image capturing function by using a computer sentence with a data grabbing function (such as a java sentence, a python sentence, etc.), wherein the data storage area includes, but is not limited to, a database, a blockchain node, and a network cache.
In one practical application scene of the invention, the obtained first image of the preset area possibly contains storage areas of the plurality of articles, and the areas for storing the logistics articles such as logistics storage, express delivery collection points and the like are regular under normal conditions, and each article has a separate storage area (such as each article grid on a goods shelf), so that the first image can be divided into a plurality of first image areas according to the preset size, the division of each article in the image is realized, the detailed image analysis of the first image is avoided, and the efficiency of the subsequent analysis of whether the articles are signed or not is improved.
In an embodiment of the present invention, the dividing the first frame into a plurality of first image areas according to a preset size includes:
generating an image frame according to the preset size;
And carrying out non-repeated frame selection on the areas in the first picture by utilizing the image frame until all the areas in the first picture are frame-selected, so as to obtain a plurality of first image areas.
In detail, the preset size may be data such as a length and a width of the area stored in each article in the first screen, which are acquired in advance.
Specifically, an image frame may be generated according to the preset size, and then non-repeated selection may be performed in the first frame by using the generated image frame, so as to obtain a plurality of first image areas.
For example, if the length of the first frame is 10cm and the width of the first frame is 10cm, and the length of the image frame generated according to the preset size is 2cm and the width of the image frame is 2cm, the image frame may be used to frame 25 first image areas with the length of 2cm and the width of 2cm in the first image area.
In one embodiment of the present invention, the encoding the plurality of first image areas according to a preset encoding manner includes:
selecting a column of image areas from the plurality of first image areas one by one in a sequence from top to bottom as a target column;
Each first image region in the target column is incrementally encoded in a left-to-right order.
For example, the first image includes 5 rows and 5 columns, 25 first image areas, a first column including 5 first image areas is selected from top to bottom as a target column, each first image area in the column is encoded (e.g. 1,2, 3,4, 5) in a left to right order, and so on until each first image area in the first image is encoded.
In the embodiment of the invention, each first image area in the first image is encoded, so that the distinction of each first image area can be realized, and further, the accurate judgment of whether each article in the first image is signed or not can be realized later.
S2, selecting one of the plurality of first image areas one by one as a target area, and extracting image features of the target area.
In the embodiment of the invention, in order to accurately judge whether the objects in the different first image areas are signed or not, one of the plurality of first image areas is selected one by one as the target area, and then each selected first image area is analyzed to judge whether the objects in the area are signed or not.
In an embodiment of the present invention, the extracting the image feature of the target area includes:
generating global features of the target region according to pixel gradients in the target region;
Utilizing a preset sliding window to frame and select the regions in the target region one by one to obtain a pixel window;
generating local features of the target area according to pixel values in each pixel window;
and collecting the global features and the local features as image features of the target area.
In one embodiment of the present invention, the global features of the target region may be generated by HOG (Histogram of Oriented Gradient, direction gradient histogram), DPM (Deformable Part Model, variability component model), LBP (Local Binary Patterns, local binary pattern), or the like, or may be extracted by an artificial intelligence model with a pre-trained specific image feature extraction function, including but not limited to VGG-net model, U-net model.
In another embodiment of the present invention, referring to fig. 2, the generating the global feature of the target area according to the pixel gradient in the target area includes:
S21, counting the pixel value of each pixel point in the target area;
s22, taking the maximum pixel value and the minimum pixel value in the pixel values as parameters of a preset mapping function, and mapping the pixel value of each pixel point in the target area into a preset range by utilizing the preset mapping function;
S23, calculating pixel gradients of each row of pixels in the target area after mapping, converting the pixel gradients of each row of pixels into row vectors, and splicing the row vectors into global features of the target area.
Illustratively, the preset mapping function may be:
Wherein, Is the first in the target areaThe pixel points are mapped to pixel values within a preset range,Is the first in the target areaThe pixel values of the individual pixel points,For the maximum pixel value in the target region,Is the minimum pixel value in the target area.
Further, the pixel gradient of each row of pixels in the target region after mapping may be calculated using a preset gradient algorithm, including but not limited to a two-dimensional discrete derivative algorithm, soble operator, and the like.
In the embodiment of the application, the pixel gradient of each row of pixels can be converted into the row vector and spliced into the global feature of the target area.
For example, the selected target region includes three rows of pixels, the first row of pixels having a pixel gradient ofThe pixel gradient of the first row of pixels isThe pixel gradient of the first row of pixels isThe pixel gradient of each row of pixels can be respectively used as a row vector to be spliced into the following global features:
further, referring to fig. 3, the generating the local feature of the target area according to the pixel value in each pixel window includes:
S31, selecting one pixel point from the pixel window one by one as a target pixel point;
s32, judging whether the pixel value of the target pixel point is an extremum in the pixel window;
Returning to S31 when the pixel value of the target pixel point is not an extremum in the pixel window;
When the pixel value of the target pixel point is an extremum in the pixel window, S33 is executed, and the target pixel point is determined to be a key point;
s34, vectorizing pixel values of all key points in all pixel windows, and collecting the obtained vectors as local features of the target area.
In the embodiment of the present application, the sliding window may be a pre-constructed selection frame with a certain area, which may be used to frame the pixels in the target area, for example, a square selection frame constructed with 10 pixels as a height and 10 pixels as a width.
In detail, the extremum includes a maximum value and a minimum value, and when the pixel value of the target pixel point is the maximum value or the minimum value in the pixel window, the target pixel point is determined to be the key point of the pixel window.
Specifically, the step of vectorizing the pixel values of all the key points in the pixel window is consistent with the step of calculating the pixel gradient of each row of pixels in the mapped target area and converting the pixel gradient of each row of pixels into a row vector, which is not described again.
S3, acquiring a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the second image areas according to a preset encoding mode.
In the embodiment of the present invention, the step of obtaining the monitoring picture of the preset area at the second moment as the second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the plurality of second image areas according to the preset encoding mode is identical to the step of obtaining the monitoring picture of the preset area at the first moment as the first picture in S1, dividing the first picture into a plurality of first image areas according to the preset size, and encoding the plurality of first image areas according to the preset encoding mode, which is not repeated herein.
S4, selecting an area with the same number as the target area from the second image area as an area to be compared, and extracting image features of the area to be compared.
In the embodiment of the present invention, the step of selecting, from the second image area, an area having the same number as the target area as the area to be compared, and extracting the image features of the area to be compared is consistent with the step of selecting, in S2, one area from the plurality of image areas one by one as the target area, and extracting the image features of the target area, which is not described herein.
S5, calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared.
In the embodiment of the invention, whether the object in the target area is signed or not can be judged according to the difference value by calculating the difference value between the image characteristic of the target non-language and the image characteristic of the area to be compared.
In the embodiment of the present invention, the calculating a difference value between the image feature of the target area and the image feature of the area to be compared includes:
Calculating a first difference value between the global feature of the target area and the global feature of the area to be compared by using a preset first distance algorithm;
Calculating a second difference value between the local features of the target area and the local features of the area to be compared by using a preset second distance algorithm;
And calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared according to the first difference value and the second difference value by using a preset weight algorithm.
In detail, the calculating, by using a preset first distance algorithm, a first difference value between the global feature of the target area and the global feature of the area to be compared includes:
calculating a first difference value between the global feature of the target region and the global feature of the region to be compared by using the following distance value algorithm:
Wherein, For the value of the first difference,As a global feature of the target region,Is a global feature of the region to be compared.
In other embodiments of the present invention, the first difference value between the global feature of the target area and the global feature of the area to be compared may also be calculated by using an algorithm such as a euclidean distance algorithm or a cosine distance algorithm.
In the embodiment of the present invention, the step of calculating the second difference value between the local feature of the target area and the local feature of the area to be compared by using a preset second distance algorithm is consistent with the step of calculating the first difference value between the global feature of the target area and the global feature of the area to be compared by using a preset first distance algorithm, which is not described herein, wherein the second distance algorithm may be the same as the first distance algorithm.
In the embodiment of the present invention, the calculating, by using a preset weight algorithm, a difference value between an image feature of the target area and an image feature of the area to be compared according to the first difference value and the second difference value includes:
Calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared according to the first difference value and the second difference value by using the following weight algorithm method:
Wherein, As a difference value between the image features of the target region and the image features of the region to be compared,For the value of the first difference,Is the second difference value.
S6, judging whether the difference value is larger than a preset difference threshold value.
In the embodiment of the invention, the calculated difference value can be compared with the preset difference threshold value, so as to judge whether the goods stored in the target area are signed or not according to the comparison result.
In the embodiment of the invention, the global and local analysis of the target area and the area to be compared is realized by respectively calculating the first difference value and the second difference value between the global feature of the target area and the global feature and the local feature of the area to be compared and calculating the difference value between the image feature of the target area and the image feature of the area to be compared by using the first difference value and the second difference value, thereby being beneficial to improving the accuracy of judging whether the goods stored in the target area are signed or not.
And when the difference value is smaller than or equal to the difference threshold value, executing S7, and determining that the goods stored in the target area are not signed.
In the embodiment of the present invention, when the difference value is smaller than or equal to the difference threshold, it is indicated that the goods in the image of the target area do not change, that is, it is determined that the goods stored in the target area are not signed.
And when the difference value is larger than the difference threshold value, executing S8, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
In the embodiment of the present invention, when the difference value is greater than the difference threshold, it is indicated that the goods in the image of the target area change, that is, it is determined that the goods stored in the target area have been signed.
In the embodiment of the invention, after the goods stored in the target area are determined to be signed, the addressee information corresponding to the goods stored in the target area can be inquired from the pre-acquired information table, and then the addressee of the goods is reminded in a mode of short message, telephone and the like according to the addressee information.
According to the embodiment of the invention, the image of the sequential time point of the area where the article is stored can be subjected to feature extraction, so that whether the article stored in the area where the article is stored is signed by a user or not is judged according to the image features corresponding to the image captured on the sequential time point, and further, the user is directly signed and reminded, confirmation or operation is not needed by the user, the non-sense signing is realized, and the article signing flow is simplified. Therefore, the object signing method based on image recognition can solve the problem of lengthy process of signing objects.
Fig. 4 is a functional block diagram of an article signing device based on image recognition according to an embodiment of the present invention.
The article signing device 100 based on image recognition according to the present invention may be installed in an electronic device. Depending on the implementation, the article signing device 100 based on image recognition may include a first image dividing module 101, a first feature extraction module 102, a second image dividing module 103, a second feature extraction module 104, and a signing judgment module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the first image dividing module 101 is configured to obtain a monitoring picture of a preset area at a first moment as a first picture, divide the first picture into a plurality of first image areas according to a preset size, and encode the plurality of first image areas according to a preset encoding mode;
The first feature extraction module 102 is configured to select one of the plurality of first image areas one by one as a target area, and extract image features of the target area;
The second image dividing module 103 is configured to obtain a second picture that is a monitoring picture of the preset area at a second moment, divide the second picture into a plurality of second image areas according to the preset size, and encode the plurality of second image areas according to a mode of encoding with the preset;
The second feature extraction module 104 is configured to select, from the second image areas, an area with the same number as the target area as an area to be compared, and extract image features of the area to be compared;
the signing judgment module 105 is configured to calculate a difference value between the image feature of the target area and the image feature of the area to be compared, and judge whether the difference value is greater than a preset difference threshold; when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed; and when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
In detail, each module in the image recognition-based article signing device 100 in the embodiment of the present invention adopts the same technical means as the image recognition-based article signing method described in fig. 1 to 3, and can produce the same technical effects, which are not described herein.
Fig. 5 is a schematic structural diagram of an electronic device for implementing an article signing method based on image recognition according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as an image recognition based item signoff program.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, executes an article signing program based on image recognition, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only for storing application software installed in an electronic device and various types of data, such as codes of an article signing program based on image recognition, but also for temporarily storing data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 5 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 5 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The image recognition based item signing program stored in the memory 11 of the electronic device 1 is a combination of instructions which, when executed in the processor 10, may implement:
Acquiring a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
Selecting one of the first image areas one by one as a target area, and extracting image features of the target area;
Acquiring a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the second image areas according to a preset encoding mode;
Selecting a region with the same number as the target region from the second image region as a region to be compared, and extracting image features of the region to be compared;
calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared, and judging whether the difference value is larger than a preset difference threshold value or not;
when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed;
And when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
Acquiring a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
Selecting one of the first image areas one by one as a target area, and extracting image features of the target area;
Acquiring a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the second image areas according to a preset encoding mode;
Selecting a region with the same number as the target region from the second image region as a region to be compared, and extracting image features of the region to be compared;
calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared, and judging whether the difference value is larger than a preset difference threshold value or not;
when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed;
And when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The blockchain (Blockchain), essentially a de-centralized database, is a string of data blocks that are generated in association using cryptographic methods, each of which contains information from a batch of network transactions for verifying the validity (anti-counterfeit) of its information and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Wherein artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) is the theory, method, technique, and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend, and expand human intelligence, sense the environment, acquire knowledge, and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (6)
1. An article signing method based on image recognition, the method comprising:
Acquiring a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
Selecting one of the first image areas one by one as a target area, and extracting image features of the target area;
Acquiring a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the second image areas according to a preset encoding mode;
Selecting a region with the same number as the target region from the second image region as a region to be compared, and extracting image features of the region to be compared;
calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared, and judging whether the difference value is larger than a preset difference threshold value or not;
when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed;
when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information;
Wherein the extracting the image feature of the target area includes: generating global features of the target region according to pixel gradients in the target region; utilizing a preset sliding window to frame and select the regions in the target region one by one to obtain a pixel window; generating local features of the target area according to pixel values in each pixel window; collecting the global features and the local features as image features of the target region;
The generating the global feature of the target region according to the pixel gradient in the target region includes: counting the pixel value of each pixel point in the target area; taking the maximum pixel value and the minimum pixel value in the pixel values as parameters of a preset mapping function, and mapping the pixel value of each pixel point in the target area into a preset range by utilizing the preset mapping function; calculating the pixel gradient of each row of pixels in the target area after mapping, converting the pixel gradient of each row of pixels into row vectors, and splicing the row vectors into global features of the target area;
The generating the local feature of the target area according to the pixel value in each pixel window comprises the following steps: selecting one pixel point from the pixel window one by one as a target pixel point; judging whether the pixel value of the target pixel point is an extremum in the pixel window; when the pixel value of the target pixel point is not an extremum in the pixel window, returning to the step of selecting one pixel point from the pixel window one by one as the target pixel point; when the pixel value of the target pixel point is an extremum in the pixel window, determining the target pixel point as a key point; vectorizing pixel values of all key points in all pixel windows, and collecting the obtained vectors as local features of the target area;
The calculating a difference value between the image feature of the target area and the image feature of the area to be compared comprises: calculating a first difference value between the global features of the target area and the global features of the area to be compared by using a preset first distance algorithm; calculating a second difference value between the local features of the target area and the local features of the area to be compared by using a preset second distance algorithm; and calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared according to the first difference value and the second difference value by using a preset weight algorithm.
2. The method for signing an article based on image recognition as set forth in claim 1, wherein said dividing said first screen into a plurality of first image areas according to a preset size comprises:
generating an image frame according to the preset size;
the image frames are utilized to carry out non-repeated frame selection on the areas in the first picture until all the areas in the first picture are frame-selected, and a plurality of first image areas are obtained;
the preset size is the length and width data of the area stored by each article in the first picture, which are acquired in advance.
3. The method for signing an article based on image recognition as set forth in claim 1, wherein said encoding said plurality of first image areas according to a predetermined encoding scheme comprises:
selecting a column of image areas from the plurality of first image areas one by one in a sequence from top to bottom as a target column;
Each first image region in the target column is incrementally encoded in a left-to-right order.
4. An image recognition-based article signing apparatus for implementing the image recognition-based article signing method as claimed in any one of claims 1 to 3, characterized in that the apparatus comprises:
The first image dividing module is used for obtaining a monitoring picture of a preset area at a first moment as a first picture, dividing the first picture into a plurality of first image areas according to a preset size, and encoding the plurality of first image areas according to a preset encoding mode;
the first feature extraction module is used for selecting one of the plurality of first image areas one by one as a target area and extracting image features of the target area;
the second image dividing module is used for obtaining a monitoring picture of the preset area at a second moment as a second picture, dividing the second picture into a plurality of second image areas according to the preset size, and encoding the plurality of second image areas according to a preset encoding mode;
The second feature extraction module is used for selecting a region with the same number as the target region from the second image region as a region to be compared and extracting the image features of the region to be compared;
The signing judging module is used for calculating a difference value between the image characteristics of the target area and the image characteristics of the area to be compared and judging whether the difference value is larger than a preset difference threshold value or not; when the difference value is smaller than or equal to the difference threshold value, determining that the goods stored in the target area are not signed; and when the difference value is larger than the difference threshold value, determining that the goods stored in the target area are signed, inquiring the addressee information of the goods stored in the target area, and reminding the addressee of the goods according to the addressee information.
5. An electronic device, the electronic device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the image recognition-based item signing method of any one of claims 1 to 3.
6. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the image recognition-based item signing method of any one of claims 1 to 3.
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| US10636168B2 (en) * | 2015-06-12 | 2020-04-28 | Sony Corporation | Image processing apparatus, method, and program |
| CN109934218A (en) * | 2019-01-22 | 2019-06-25 | 阿里巴巴集团控股有限公司 | A kind of recognition methods and device for logistics single image |
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