CN102646312B - Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing - Google Patents
Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing Download PDFInfo
- Publication number
- CN102646312B CN102646312B CN 201210146633 CN201210146633A CN102646312B CN 102646312 B CN102646312 B CN 102646312B CN 201210146633 CN201210146633 CN 201210146633 CN 201210146633 A CN201210146633 A CN 201210146633A CN 102646312 B CN102646312 B CN 102646312B
- Authority
- CN
- China
- Prior art keywords
- video
- frame
- piece
- distributed
- recognition result
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Image Analysis (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
The invention discloses a forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing. The method comprises the following steps of: uniformly segmenting an image of each frame in video stream into video blocks with the width being W and the height being H, carrying out distributed-calculation distribution and recovery on all video blocks, fully utilizing all computing resources, supporting and processing monitoring and recognition of the characteristics of smoke and fire of large-scale video stream. The forest smoke-fire monitoring and recognizing method disclosed by the invention has the advantages that the large-scale video stream can be conveniently concentrated, and by extraction and grouping of frames, the computing resources can be submitted to a distributed computing platform for unified management and parallel recognition algorithm processing, so that the recognizing and processing capabilities are enhanced; for the detailed recognition process, the extracted image frames are segmented, the characteristic threshold can be flexibly set, and the recognition sensitivity is controlled, so that the efficiency and the accuracy of forest smoke-fire monitoring and recognition are improved.
Description
Technical field
The present invention relates to the Computer Applied Technology field, especially based on forest fire monitoring and the method for early warning of Digital Image Processing and pyrotechnics identification.
Background technology
At forest fire monitoring and warning aspect, the multiple technologies means have been adopted all over the world at present.Forest department at county level has mainly adopted the real-time video monitoring method of emphasis fire hazard zone to China recent years in the city.
Be that the patent of invention of representative provides a kind of forest fire preventing monitor system Integrated Solution based on real-time video with application number 02135403.0.Can make up the concentrated supervision of the forest fire protection real-time video in a certain zone based on this scheme, say it is a kind of progress technically, can play the excellent prevention effect to the monitoring of forest fire by real-time video monitoring.But this scheme need drop into great amount of manpower and watch video in real time, causes naked eyes fatigue easily, and the condition of a fire in the video is omitted, and has also reflected the common fault of traditional video surveillance.
Application number provides a kind of control point setting based on the electrode voltage variation monitoring to make up monitoring network for the forest fire protection monitoring with transmission for 201010278993.0 patent of invention.This scheme implementation cost is lower, but the monitor staff can't further confirm monitoring effect when false positive signal.Along with development of digital image, correlation technique is suggested and be used for realizes intelligent video monitoring.
Application number is that 200810127874.8 patent of invention will transplant that monitoring image is identified early warning based on the recognizer of image RGB, but rate of false alarm is higher.
As a kind of improved technology, application number is that 200910086691.0 patent of invention has been carried out mask to skip over the analysis in this zone at the normal easy interference region that occurs in the forest zone, can reduce its practical value undoubtedly but only get rid of interference by mask in the Protean applied environment of reality.
Application number is that 201010188231.1 patent of invention moves forward recognizer, has increased the front end embedded device, has reduced the image quality decrease that causes owing to the network transmission to the influence of recognition effect.This scheme has focused on providing a kind of Programmable Technology to front-end equipment, and recognition efficiency and effect effectively do not promote, and has increased the cost of system's construction.
Intelligent video monitoring based on graphical analysis and processing is the developing direction of following forest fire protection early warning, can early find, early warning early, can realize the unmanned of large-range monitoring simultaneously.Because the early sign of fire mainly is the smog of variform and less naked light, and along with varying also can appear in factors such as different regions, season, weather, therefore, the algorithm that pyrotechnics is identified has proposed very harsh requirement.In the actual use system; risk of forest fire guarded region in certain administrative division can be formed by being distributed in the favourable a plurality of control points of each landform usually; and return step by step by network and to gather; especially be to be aggregated into after the provincial forestry competent authorities; need simultaneously treated video way may reach the hundreds of road; thereby make the information processing centre of administrative authoritys at different levels need simultaneously treated live video stream data volume huge, the computing power of moving recognizer has also been proposed very high requirement.
At the problem that exists in existing forest fire alarm monitoring based on real-time video and the early warning system, this area demands occurring corresponding solution urgently.
Summary of the invention
The purpose of this invention is to provide a kind of forest rocket monitoring and recognition methods that is applicable to that distributed parallel is handled, this method is by carrying out grouped record and cutting frame by frame after all video flowings are concentrated, form an organism from the logical layer tissue then, submit to the Distributed Calculation platform.Because the Distributed Calculation platform can calculate cluster from logic many computing machines being formed one, effectively organizes computational resource, is fit to carry out large-scale calculations, therefore, can well handle the pyrotechnics recognizer of the extensive video flowing of multichannel in this programme.
Technical scheme of the present invention is a kind of forest rocket monitoring recognition methods that distributed parallel is handled that is suitable for, and may further comprise the steps:
Step 1 to video flowing intercepting frame of video, is carried out the ID distribution and is added a cover timestamp each frame of video of intercepting gained, and wherein ID is that same ID number frame of video constitutes a frame of video group for the identification code in the source of sign video flowing;
Step 2 is carried out pyrotechnics feature identification processing respectively to all frame of video groups that step 1 obtains, and is returned recognition result as the early warning foundation; The realization of arbitrary frame of video group being carried out pyrotechnics feature identification processing comprises following substep,
Step 2.1 sorts all frame of video in the frame of video group and distributes frame number i according to time order and function that timestamp provides, establish all frame of video V in arbitrary frame of video group
iAdd up to n+1, i=0,1..n;
Step 2.2 is with all the frame of video V in the frame of video group
iBe evenly divided into the video piece that is of a size of W * H, setting video frame V
iIn all video piece B
IjAdd up to m+1, j=0,1..m;
Step 2.3 is to arbitrary frame of video V
iAll video piece B that are divided into
IjCarry out following steps,
Step 2.3.1 judges whether i waits 0, is store video piece B then
0j, otherwise enter step 2.3.2;
Step 2.3.2 calculates video piece B
IjIn satisfy condition | B
Ij(w, h)-B
0j(w, h) |〉the number N of the pixel of T, wherein B
Ij(w h) is video piece B
IjMiddle horizontal ordinate is the gray values of pixel points of h for the w ordinate, w=1, and 2..W, h=1,2..H, T is default gray threshold;
Step 2.3.3 judges that (W * H) whether greater than p, wherein p is default motor image vegetarian refreshments percentage threshold to N/; Be then to enter step 2.3.4, otherwise this video piece of mark B
IjRecognition result R
Ij=false;
Step 2.3.4 calculates video piece B
IjIn satisfy the number M of the pixel of following three conditions simultaneously
|B
ij(w,h)-B
ij(w+1,h)﹤?V
|B
ij(w,h)-B
ij(w,h+1)﹤V
|B
ij(w,h)-B
ij(w+1,h+1)|﹤V
Wherein, V is default blur level threshold value;
Step 2.3.5 judges that (W * H) whether greater than q, wherein q is default vague image vegetarian refreshments percentage threshold to M/; Be marking video piece B then
IjRecognition result R
Ij=true, otherwise this video piece of mark B
IjRecognition result R
Ij=false;
Step 2.4 is to step 2.3 gained frame of video V
iAll video piece B that are divided into
IjRecognition result R
IjMerge processing, obtain frame of video V
iRecognition result R
i
And, the cluster server of disposing the Distributed Calculation platform is set, the Distributed Calculation platform is distributed all frame of video groups that step 1 obtains, and distributed parallel carries out the identification of pyrotechnics feature to be handled.
And the Distributed Calculation platform is to arbitrary frame of video V
iAll video piece B that are divided into
IjCarry out distributed parallel and handle, realize execution in step 2.3.
The present invention can be in conjunction with user's actual environment and experience, set the sensitivity of identification, carry out enough measuring and calculating at the valid frame in the video flowing, remedy the identification error that causes owing to reasons such as capturing video quality in the actual monitored system, strengthened the effect of identification.The technical solution adopted in the present invention is divided into groups the picture frame that extracts in all video flowings ID according to video source, identification processing procedure is relatively independent, the system of being suitable for unifies scheduling, distributing to different computational resources handles, last only the need records effective recognition result and return, and is specially adapted to utilize distributed platform to carry out large-scale video identification.
Description of drawings
Fig. 1 is the pyrotechnics identification process figure of the embodiment of the invention.
Fig. 2 is the application architecture model of the embodiment of the invention.
Embodiment
The present invention is a kind of pyrotechnics characteristic recognition method that is applicable to large-scale distributed parallel processing in the forest fire protection real-time video monitoring system.
Describe technical solution of the present invention in detail below in conjunction with drawings and Examples.Referring to Fig. 1, the flow process of embodiment may further comprise the steps:
Step 1 to video flowing intercepting frame of video, is carried out the ID distribution and is added a cover timestamp each frame of video of intercepting gained, and wherein ID is that same ID number frame of video constitutes a frame of video group for the identification code in the source of sign video flowing.
The video flowing of embodiment intercepts by certain spacing frequency (as intercepting a frame every 5 frames), and the ID number conduct grouping foundation unique to the source distribution of each front end control point, add a cover timestamp simultaneously to distinguish the frame of video group of different time node under the same ID.
Step 2 is carried out pyrotechnics feature identification processing respectively to all frame of video groups that step 1 obtains, and is returned recognition result as the early warning foundation; The realization of arbitrary frame of video group being carried out pyrotechnics feature identification processing comprises following substep,
Step 2.1 sorts all frame of video in the frame of video group and distributes frame number i according to time order and function that timestamp provides, establish all frame of video V in arbitrary frame of video group
iAdd up to n+1, i=0,1..n;
Step 2.2 is with all the frame of video V in the frame of video group
iBe evenly divided into the video piece that is of a size of W * H, setting video frame V
iIn all video piece B
IjAdd up to m+1, j=0,1..m; All between 10 to 20, the embodiment value is 10 to the suggestion value of W and H;
Step 2.3 is to arbitrary frame of video V
iAll video piece B that are divided into
IjCarry out following steps,
Step 2.3.1 judges whether i waits 0, is store video piece B then
0j, stop video piece B
0jHandle, otherwise enter step 2.3.2; The present invention is with the first frame frame of video V in the frame of video group
0Frame as a setting, store video piece B
0jTreat that the subsequent dynamic frame detects video piece B
IjIn time, use, i=1,2..n;
Step 2.3.2 calculates video piece B
IjIn satisfy condition | B
Ij(w, h)-B
0j(w, h) |〉the number N of the pixel of T, wherein B
Ij(w h) is video piece B
IjMiddle horizontal ordinate is the gray values of pixel points of h for the w ordinate, B
0j(w h) is video piece B
0jMiddle same position gray values of pixel points, w=1,2..W, h=1,2..H, T is default gray threshold; B
Ij(T is default gray threshold for w, h) value between 0 to 255, between the suggestion value 25 to 30;
Step 2.3.3 judges that (W * H) whether greater than p, wherein p is default motor image vegetarian refreshments percentage threshold (embodiment gets 30% for empirical value, suggestion value 10% to 30%) to N/; Be then to enter step 2.3.4, otherwise this video piece of mark B
IjRecognition result R
Ij=false is right;
Step 2.3.4 calculates video piece B
IjIn satisfy the number M of the pixel of following three conditions simultaneously
|B
ij(w,h)-B
ij(w+1,h)|﹤V
|B
ij(w,h)-B
ij(w,h+1)|﹤V
|B
ij(w,h)-B
ij(w+1,h+1)|﹤V
Embodiment is with the gray-scale value B of current pixel point
Ij(w, h) the gray-scale value B of neighborhood right with it, following neighborhood and bottom right neighborhood territory pixel point
Ij(w+1, h), B
Ij(w, h+1), B
Ij(w+1 h+1) carries out calculus of differences respectively, and the branch computing result that is on duty judges that then this pixel is litura during all less than default blur level threshold value V; The suggestion value of blur level threshold value V is 50;
Step 2.3.5 judges that (W * H) whether greater than q, wherein q is default vague image vegetarian refreshments percentage threshold (empirical value, suggestion gets 70%) to M/; Be marking video piece B then
IjRecognition result R
Ij=true, otherwise this video piece of mark B
IjRecognition result R
Ij=false;
Step 2.4 is to step 2.3 gained frame of video V
iAll video piece B that are divided into
IjRecognition result R
IjMerge processing, obtain frame of video V
iRecognition result R
iEmbodiment reclaims merging according to frame number i, and amalgamation result can be submitted to as the early warning foundation.
The method of the present invention's design is suitable for distributed parallel and handles, in order to raise the efficiency, can adopt existing Distributed Calculation platform technology, by the Distributed Calculation platform all frame of video groups that step 1 obtains be distributed, distributed parallel carries out the identification of pyrotechnics feature to be handled.As shown in Figure 1, the present invention can be to all the frame of video V in the frame of video group
iHandle one by one, flow process can be designed to first initialization i=0, after the execution in step 2.4, carries out i=i+1, up to i=n.For the purpose of raising the efficiency, also can get frame of video V earlier
0Behind background frames, to other all the frame of video V in the frame of video group
i(i=1,2..n) also distributed parallel is handled.The Distributed Calculation platform is to arbitrary frame of video V
iAll video piece B that are divided into
IjAlso can further carry out distributed parallel and handle, realize execution in step 2.3.
Referring to Fig. 2, H.264 the name a person for a particular job real-time video of camera acquisition of each front end video signal collective is transmitted through the network to information center behind the standard code through video encoder.Can adopt multiple transmission modes such as microwave, optical fiber, 3G according to actual conditions, switch access information center can be set.According to the system scale size, will there be N road front-end collection point to converge to information center.In the reality, information center has generally disposed function servers such as storage server, management server, streaming media server, decoding server by LAN (Local Area Network), and connect some clients, all are from the video flowing inlet flow media server of front end, and information center's gained data can upload to the internet by router.The embodiment of the invention proposes to arrange cluster server, dispose the Distributed Calculation platform at cluster server, specific implementation is prior art, as the application platform based on the DCOM standard of the CORBA standard of OMG or Microsoft, will be in the operation that is scheduled of this platform based on the identification handling procedure of technique scheme.Streaming media server gained video flowing carries out distributed parallel at cluster server to be handled, all video flowings divided record back on cluster server is allocated according to the computational resource in the network and is distributed to different computational resources, because the unified scheduling of Distributed Calculation platform, these computational resources are from being considered to an integral body in logic, thereby make the computational resource in the present networks be fully utilized, with large-scale video data in the disposal system.It is true that the recognizer program is returned as true() frame of video V
iAffiliated packet ID, can judge this group and have the picture frame of pyrotechnics feature from which control point of front end, and the relevant satellite information that can further comprise according to this picture group picture frame, as information such as the The Cloud Terrace angle of correspondence (level, vertical), lens focus, to identify to such an extent that pyrotechnics information is precisely located.Follow-up early warning is handled can be by the management server specific implementation, and the present invention will not give unnecessary details.
Specific embodiment described herein only is that the present invention's spirit is illustrated.Those skilled in the art can make various modifications or replenish or adopt similar mode to substitute described specific embodiment, for example each threshold value can be set voluntarily as the case may be by those skilled in the art, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.
Claims (2)
1. one kind is suitable for the forest rocket monitoring recognition methods that distributed parallel is handled, and it is characterized in that: may further comprise the steps:
Step 1 to video flowing intercepting frame of video, is carried out the ID distribution and is added a cover timestamp each frame of video of intercepting gained, and wherein ID is that same ID number frame of video constitutes a frame of video group for the identification code in the source of sign video flowing;
Step 2 arranges the cluster server of disposing the Distributed Calculation platform, and the Distributed Calculation platform is distributed all frame of video groups that step 1 obtains, and distributed parallel carries out the identification of pyrotechnics feature to be handled, and returns recognition result as the early warning foundation; The realization of arbitrary frame of video group being carried out pyrotechnics feature identification processing comprises following substep,
Step 2.1 sorts all frame of video in the frame of video group and distributes frame number i according to time order and function that timestamp provides, establish all frame of video V in arbitrary frame of video group
iAdd up to n+1, i=0,1..n;
Step 2.2 is with all the frame of video V in the frame of video group
iBe evenly divided into the video piece that is of a size of W * H, setting video frame V
iIn all video piece B
IjAdd up to m+1, j=0,1..m;
Step 2.3 is to arbitrary frame of video V
iAll video piece B that are divided into
IjCarry out following steps,
Step 2.3.1 judges whether i waits 0, is store video piece B then
0j, otherwise enter step 2.3.2;
Step 2.3.2 calculates video piece B
IjIn satisfy condition | B
Ij(w, h)-B
0j(w, h) |〉the number N of the pixel of T, wherein B
Ij(w h) is video piece B
IjMiddle horizontal ordinate is the gray values of pixel points of h for the w ordinate, w=1, and 2..W, h=1,2..H, T is default gray threshold;
Step 2.3.3 judges that (W * H) whether greater than p, wherein p is default motor image vegetarian refreshments percentage threshold to N/; Be then to enter step 2.3.4, otherwise this video piece of mark B
IjRecognition result R
Ij=false;
Step 2.3.4 calculates video piece B
IjIn satisfy the number M of the pixel of following three conditions simultaneously
|B
ij(w,h)-B
ij(w+1,h)|﹤V
|B
ij(w,h)-B
ij(w,h+1)|﹤V
|B
ij(w,h)-B
ij(w+1,h+1)|﹤V
Wherein, V is default blur level threshold value;
Step 2.3.5 judges that (W * H) whether greater than q, wherein q is default vague image vegetarian refreshments percentage threshold to M/; Be marking video piece B then
IjRecognition result R
Ij=true, otherwise this video piece of mark B
IjRecognition result R
Ij=false;
Step 2.4 is to step 2.3 gained frame of video V
iAll video piece B that are divided into
IjRecognition result R
IjMerge processing, obtain frame of video V
iRecognition result R
i
2. be suitable for the forest rocket monitoring recognition methods that distributed parallel is handled according to claim 1, it is characterized in that: the Distributed Calculation platform is to arbitrary frame of video V
iAll video piece B that are divided into
IjCarry out distributed parallel and handle, realize execution in step 2.3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210146633 CN102646312B (en) | 2012-05-11 | 2012-05-11 | Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210146633 CN102646312B (en) | 2012-05-11 | 2012-05-11 | Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102646312A CN102646312A (en) | 2012-08-22 |
| CN102646312B true CN102646312B (en) | 2013-08-14 |
Family
ID=46659123
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201210146633 Active CN102646312B (en) | 2012-05-11 | 2012-05-11 | Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102646312B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103248705B (en) * | 2013-05-20 | 2016-03-23 | 北京智谷睿拓技术服务有限公司 | Server, client and method for processing video frequency |
| CN104408469A (en) * | 2014-11-28 | 2015-03-11 | 武汉大学 | Firework identification method and firework identification system based on deep learning of image |
| CN104715559B (en) * | 2015-03-06 | 2018-07-27 | 温州大学 | A kind of Smoke Detection and fire alarm method based on track identification |
| CN112037593A (en) * | 2019-06-03 | 2020-12-04 | 广东小天才科技有限公司 | Learning interaction implementation method and system based on augmented reality |
| CN113516006A (en) * | 2021-04-01 | 2021-10-19 | 广州云硕科技发展有限公司 | Efficient information processing method and system for intelligent robot |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100858140B1 (en) * | 2007-02-20 | 2008-09-10 | (주)에이치엠씨 | Method and system for detecting a fire by image processing |
| US7786877B2 (en) * | 2008-06-20 | 2010-08-31 | Billy Hou | Multi-wavelength video image fire detecting system |
| CN101373553B (en) * | 2008-10-23 | 2010-06-16 | 浙江理工大学 | Early-stage smog video detecting method capable of immunizing false alarm in dynamic scene |
| KR101044903B1 (en) * | 2009-04-28 | 2011-06-28 | 부산대학교 산학협력단 | Fire detecting method using hidden markov models in video surveillance and monitoring system |
| CN101587622B (en) * | 2009-06-18 | 2012-09-05 | 李秋华 | Forest rocket detecting and identifying method and apparatus based on video image intelligent analysis |
| CN101872526B (en) * | 2010-06-01 | 2012-04-18 | 重庆市海普软件产业有限公司 | Smoke and fire intelligent identification method based on programmable photographing technology |
| CN102163358B (en) * | 2011-04-11 | 2012-07-04 | 杭州电子科技大学 | Smoke/flame detection method based on video image analysis |
-
2012
- 2012-05-11 CN CN 201210146633 patent/CN102646312B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN102646312A (en) | 2012-08-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9002060B2 (en) | Object retrieval in video data using complementary detectors | |
| CN102646312B (en) | Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing | |
| CN103839308B (en) | Number acquisition methods, Apparatus and system | |
| CN106845415B (en) | Pedestrian fine identification method and device based on deep learning | |
| CN111582016A (en) | Intelligent maintenance-free power grid monitoring method and system based on cloud edge collaborative deep learning | |
| CN103279949A (en) | Operation method of self-positioning robot-based multi-camera parameter automatic calibration system | |
| CN103069434A (en) | Multi-mode video event indexing | |
| CN106682592A (en) | Automatic image recognition system and method based on neural network method | |
| CN108683877A (en) | Distributed massive video resolution system based on Spark | |
| CN110659391A (en) | Video detection method and device | |
| US10685443B2 (en) | Cloud detection using images | |
| CN114665608B (en) | Intelligent sensing inspection system and method for transformer substation | |
| CN104134067A (en) | Road vehicle monitoring system based on intelligent visual Internet of Things | |
| CN110087041B (en) | Video data processing and transmitting method and system based on 5G base station | |
| CN103888731A (en) | Structured description device and system for mixed video monitoring by means of gun-type camera and dome camera | |
| CN111291646A (en) | People flow statistical method, device, equipment and storage medium | |
| CN114170569A (en) | Method, system, storage medium and equipment for monitoring road surface abnormal condition | |
| CN116760884B (en) | Ocean big data cloud service system and application method | |
| CN113792106A (en) | Road state updating method and device, electronic equipment and storage medium | |
| CN113349188A (en) | Lawn and forage grass precise weeding method based on cloud weeding spectrum | |
| CN116886869A (en) | Video monitoring system and video tracing method based on AI | |
| CN117423157A (en) | Mine abnormal video action understanding method combining migration learning and regional invasion | |
| Ganesh et al. | An intelligent video surveillance framework with big data management for Indian road traffic system | |
| CN116248861A (en) | Intelligent video detection method, system and device | |
| CN115565137A (en) | Improved YOLOv 5-based unsafe behavior detection and alarm method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| ASS | Succession or assignment of patent right |
Owner name: WUHAN YINKE TECHNOLOGY DEVELOPMENT CO., LTD. Free format text: FORMER OWNER: WUHAN UNIVERSITY Effective date: 20150722 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20150722 Address after: 430079, room two, 5-902 laurel garden, 428 male Chu street, Hongshan District, Hubei, Wuhan Patentee after: Wuhan inkoo Technology Development Co. Ltd. Address before: 430072 Hubei city of Wuhan province Wuchang Wuhan University Luojiashan Patentee before: Wuhan University |
|
| ASS | Succession or assignment of patent right |
Owner name: WUHAN WANDE ZHIXIN TECHNOLOGY CO., LTD. Free format text: FORMER OWNER: WUHAN YINKE TECHNOLOGY DEVELOPMENT CO., LTD. Effective date: 20150906 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20150906 Address after: 430070, No. 18, No. 1-112, Qingling Road, Wuhan Youth Industrial Zone, Hongshan District, Hubei Patentee after: Wuhan Wande chi new Polytron Technologies Inc Address before: 430079, room two, 5-902 laurel garden, 428 male Chu street, Hongshan District, Hubei, Wuhan Patentee before: Wuhan inkoo Technology Development Co. Ltd. |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A forest fireworks monitoring and recognition method suitable for distributed parallel processing Effective date of registration: 20220331 Granted publication date: 20130814 Pledgee: Bank of China Limited Wuhan Qingshan sub branch Pledgor: WUHAN WONDNET TECHNOLOGY CO.,LTD. Registration number: Y2022420000092 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |