TWM587335U - Automatic teller machine warning system - Google Patents
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Abstract
Description
本新型係關於一種自動櫃員機，尤指一種具備預警功能的自動櫃員機。The invention relates to an automatic teller machine, in particular to an automatic teller machine with a warning function.
現代社會大眾不僅可以透過自動櫃員機提款，還可以進行存款、繳費或轉帳等服務，並且自動櫃員機的據點也日益增加，著實成為現代社會大眾生活裡不可缺少的部份。現有之自動櫃員機由於僅裝設錄影設施，且錄影之影音內容係為各家金融機構所各別儲存。對於金融卡盜領案層出不窮，詐騙集團車手猖獗，以及犯案器具日益精良，現有的自動櫃員機的安全機制根本難以防範，造成金融機構及客戶的損失，亦形成社會治安的嚴重問題。The masses of modern society can not only withdraw money through ATMs, but also provide services such as deposit, payment or transfer, and the number of ATM bases is also increasing, which has become an indispensable part of the masses of modern society. The existing ATMs are only equipped with recording facilities, and the recorded video and audio contents are stored separately by each financial institution. There are endless cases of fraudulent collection of financial cards, fraudulent group drivers, and increasingly sophisticated crime instruments. The existing ATM security mechanism is difficult to prevent, causing losses to financial institutions and customers, and also a serious problem of social order.
有鑑於此，在實務上確實需要一種改良的自動櫃員機系統，至少可解決以上缺失。In view of this, there is indeed a need for an improved ATM system in practice, which can at least solve the above defects.
本新型提供一種自動櫃員機預警系統，其對於異常事件的偵測與警報機制，更能針對現今的犯罪手法，有效地避免自動櫃員機被盜領。The present invention provides an automatic teller machine early warning system. The detection and alarm mechanism for abnormal events can better target current criminal methods and effectively prevent the theft of automatic teller machines.
依據本新型的一實施例，提供一種自動櫃員機預警系統，包括自動櫃員機、影像擷取元件、臉部特徵比對單元、處理器以及警示裝置。影像擷取元件設置於自動櫃員機，影像擷取元件連續地擷取多個臉部影像。臉部特徵比對單元電性連接於影像擷取元件且判斷該些臉部影像是否具有相同的臉部特徵。當該些臉部影像具有相同臉部特徵時，臉部特徵比對單元輸出第一確認訊號。處理器電性連接臉部特徵比對單元，當臉部特徵比對單元輸出第一確認訊號時，處理器判斷該些臉部影像所跨越的總時間是否大於時間上限。當總時間大於時間上限時，處理器輸出第二確認訊號。警示裝置設置於自動櫃員機且電性連接於處理器，當處理器輸出第二確認訊號時，警示裝置讀取第二確認訊號以輸出警示訊號。According to an embodiment of the present invention, an automatic teller machine early warning system is provided, which includes an automatic teller machine, an image capturing element, a facial feature comparison unit, a processor, and a warning device. The image capturing element is set on the ATM, and the image capturing element continuously captures multiple facial images. The facial feature comparison unit is electrically connected to the image capturing component and determines whether the facial images have the same facial features. When the facial images have the same facial features, the facial feature comparison unit outputs a first confirmation signal. The processor is electrically connected to the facial feature comparison unit. When the facial feature comparison unit outputs the first confirmation signal, the processor determines whether the total time spanned by the facial images is greater than the upper time limit. When the total time is greater than the upper time limit, the processor outputs a second confirmation signal. The warning device is set on the ATM and is electrically connected to the processor. When the processor outputs a second confirmation signal, the warning device reads the second confirmation signal to output a warning signal.
本新型所提供的自動櫃員機預警系統，可以根據所偵測之臉部影像，判定操作自動櫃員機的人員是否為同一人。此外自動櫃員機更進一步紀錄金融卡於自動櫃員機之登入時間，藉此判斷金融卡於自動櫃員機的登入時間是否異常。再者，更紀錄登入自動櫃員機的相異帳號數量，藉此判斷登入自動櫃員機的金融卡數量是否異常。透過多重的判斷機制，提高處理器判斷是否發生金融盜領行為的準確率，有效地減少誤判的次數，藉此避免警示裝置在錯誤的時機發出警示訊號，造成硬體資源的浪費。The automatic teller machine early warning system provided by the new model can determine whether the person operating the automatic teller machine is the same person based on the detected face image. In addition, the ATM further records the login time of the financial card at the ATM to determine whether the login time of the financial card at the ATM is abnormal. Furthermore, the number of different accounts logged into the ATM is recorded to determine whether the number of financial cards logged into the ATM is abnormal. Through multiple judgment mechanisms, the accuracy of the processor in determining whether financial theft occurs can be effectively reduced, and the number of misjudgments can be effectively reduced, so as to prevent the warning device from issuing a warning signal at the wrong timing, causing waste of hardware resources.
以上之關於本新型內容之說明及以下之實施方式之說明係用以示範與解釋本新型之精神與原理，並且提供本新型之專利申請範圍更進一步之解釋。The above description of the content of the new model and the description of the following embodiments are used to demonstrate and explain the spirit and principle of the new model, and provide a further explanation of the scope of the patent application of the new model.
以下在實施方式中詳細敘述本新型之詳細特徵以及優點，其內容足以使任何熟習相關技藝者了解本新型之技術內容並據以實施，且根據本說明書所揭露之內容、申請專利範圍及圖式，任何熟習相關技藝者可輕易地理解本新型相關之目的及優點。以下之實施例係進一步詳細說明本新型之觀點，但非以任何觀點限制本新型之範疇。The detailed features and advantages of the new model are described in detail in the following embodiments. The content is sufficient for any person skilled in the art to understand and implement the technical content of the new model. According to the content disclosed in this specification, the scope of patent applications and the drawings Anyone skilled in related arts can easily understand the purpose and advantages of this new type. The following examples further illustrate the viewpoints of the present invention in detail, but do not limit the scope of the present invention in any way.
圖1係繪示本新型第一實施例的自動櫃員機預警系統的示意圖。如圖1所示，自動櫃員機預警系統包括自動櫃員機10以及銀行伺服主機20，其中自動櫃員機10包括讀取單元11、影像擷取元件12、警示裝置13以及第一網路連接介面14，而銀行伺服主機20包括臉部特徵比對單元21、處理器22以及第二網路連接介面23。第一網路連接介面14與第二網路連接介面23連接至網路，使得自動櫃員機10與銀行伺服主機20之間可以雙向溝通。FIG. 1 is a schematic diagram illustrating an automatic teller machine early warning system according to a first embodiment of the present invention. As shown in FIG. 1, the ATM early warning system includes an ATM 10 and a bank servo host 20. The ATM 10 includes a reading unit 11, an image capturing element 12, a warning device 13, and a first network connection interface 14. The servo host 20 includes a facial feature comparison unit 21, a processor 22, and a second network connection interface 23. The first network connection interface 14 and the second network connection interface 23 are connected to the network, so that the ATM 10 and the bank server host 20 can communicate in two directions.
自動櫃員機10的讀取單元11電性連接於影像擷取元件12及第一網路連接介面14，當自動櫃員機10的使用者***金融卡後，讀取單元11讀取金融卡帳號以輸出致能訊號至影像擷取元件12，藉此驅動影像擷取元件12擷取影像。影像擷取元件12可例如為隱藏式攝影機，且用於連續地擷取影像。影像擷取元件12設置於自動櫃員機10上的適當高度，以使影像擷取元件12的拍攝角度範圍涵蓋到自動櫃員機10的操作人員的臉部。例如，影像擷取元件12設置於自動櫃員機10的顯示螢幕的框架上。為了減少拍攝的死角，影像擷取元件12的數量可為多個且分別設置於自動櫃員機10上的不同位置，例如，多個影像擷取元件12分別設置於顯示螢幕的上側框架、左側框架、右側框架。The reading unit 11 of the ATM 10 is electrically connected to the image capturing element 12 and the first network connection interface 14. When the user of the ATM 10 inserts a financial card, the reading unit 11 reads the financial card account number and outputs the result. The energy signal is sent to the image capturing element 12 to drive the image capturing element 12 to capture an image. The image capturing element 12 may be, for example, a hidden camera, and is used for continuously capturing images. The image capturing element 12 is set at an appropriate height on the ATM 10 so that the shooting angle range of the image capturing element 12 covers the face of the operator of the ATM 10. For example, the image capturing element 12 is disposed on a frame of a display screen of the ATM 10. In order to reduce the dead angle of shooting, the number of image capturing elements 12 may be multiple and respectively disposed at different positions on the ATM 10. For example, the plurality of image capturing elements 12 are respectively arranged on the upper frame, the left frame, Right frame.
銀行伺服器20的臉部特徵比對單元21可例如為儲存有臉部辨識演算法之現場可程式化邏輯陣列(Field Programmable Gate Array, FPGA)且電性連接於處理器22與第二網路連接介面23。關於臉部特徵比對單元21的一實施例中，當人臉影像是二維影像或三維影像時，臉部特徵比對單元21從來自影像擷取元件12的每一人臉影像中取得至少一個臉部特徵 (例如眼、耳、口、鼻、臉部輪廓) 於二維空間或三維空間的形狀、位置或數個臉部特徵之間的相對位置。之後，臉部特徵比對單元21再將每一人臉影像的臉部特徵儲存於銀行伺服主機20的儲存裝置中。臉部特徵比對單元21將連續多張人臉影像的臉部特徵進行比對，若判斷該些人臉影像的臉部特徵全部相同時，則驗證該些人臉影像均為同一人而輸出第一確認訊號至處理器22。The facial feature comparison unit 21 of the bank server 20 may be, for example, a Field Programmable Gate Array (FPGA) that stores a facial recognition algorithm and is electrically connected to the processor 22 and the second network. Connection interface 23. In an embodiment of the facial feature comparison unit 21, when the face image is a two-dimensional image or a three-dimensional image, the facial feature comparison unit 21 obtains at least one from each face image from the image capturing element 12. Facial features (such as eyes, ears, mouth, nose, facial contours) The shape, position, or relative position of several facial features in two or three dimensions. After that, the facial feature comparison unit 21 stores the facial features of each face image in the storage device of the bank server host 20. The facial feature comparison unit 21 compares the facial features of multiple consecutive facial images. If it is determined that the facial features of the facial images are all the same, it is verified that the facial images are the same person and output. The first confirmation signal is sent to the processor 22.
處理器22可例如為中央處理器(CPU)、數位訊號處理器(DSP)、微處理器(MPU)、圖形處理器(GPU)或微控制器(MCU)，處理器22電性連接於第二網路連接介面23且持續紀錄每一張人臉影像出現的時間。處理器22預設有一時間上限，當處理器22接收到第一確認訊號時，處理器22判斷該些臉部影像所出現的總時間是否大於時間上限。當處理器22確認該些臉部影像出現的總時間大於預設的時間上限時，處理器22輸出第二確認訊號至第二網路連接介面23。此外，處理器22還預設一數量門檻。當處理器22確認該些臉部影像出現的總時間未大於預設的時間上限時，處理器22更進一步判斷該些臉部影像出現的時間區間內登入自動櫃員機10的相異帳號數量是否大於數量門檻。當處理器22確認登入自動櫃員機10相異帳號數量大於數量門檻時，處理器22亦輸出第二確認訊號至第二網路連接介面23。The processor 22 may be, for example, a central processing unit (CPU), a digital signal processor (DSP), a microprocessor (MPU), a graphics processor (GPU), or a microcontroller (MCU). The processor 22 is electrically connected to the first processor. The second network connection interface 23 continuously records the appearance time of each face image. The processor 22 presets a time upper limit. When the processor 22 receives the first confirmation signal, the processor 22 determines whether the total time that the facial images appear is greater than the time upper limit. When the processor 22 confirms that the total time that the facial images appear is greater than a preset time limit, the processor 22 outputs a second confirmation signal to the second network connection interface 23. In addition, the processor 22 presets a threshold. When the processor 22 confirms that the total time during which the facial images appear is not greater than the preset time limit, the processor 22 further determines whether the number of different account numbers logged into the ATM 10 within the time interval during which the facial images appear is greater than Quantity threshold. When the processor 22 confirms that the number of different accounts logged in to the ATM 10 is greater than the number threshold, the processor 22 also outputs a second confirmation signal to the second network connection interface 23.
警示裝置13電性連接於第一網路連接介面14，而當警示裝置13接收到來自處理器22的第二確認訊號後，警示裝置13輸出警示訊號。警示訊號例如包含聲音訊號以及光訊號，而光訊號具有閃爍頻率，聲音訊號可包含有具有警示意味的字串，藉此達到嚇阻的作用。The warning device 13 is electrically connected to the first network connection interface 14, and when the warning device 13 receives the second confirmation signal from the processor 22, the warning device 13 outputs a warning signal. The warning signal includes, for example, a sound signal and a light signal, and the light signal has a blinking frequency. The sound signal may include a string with a warning sign, thereby achieving a deterrent effect.
圖2係繪示本新型第二實施例的自動櫃員機預警系統的示意圖。圖2的實施例與圖1的實施例大部分相同，差異在於臉部特徵比對單元15與處理器16直接設置於自動櫃員機10，省去自動櫃員機10經由網路傳遞資料至銀行伺服主機20的時間。也因為資料傳遞不需透過網路連線，所以即使自動櫃員機10與銀行伺服主機20之間的網路連線發生故障，自動櫃員機10上的預警機制依然可正常的運作。FIG. 2 is a schematic diagram illustrating an automatic teller machine early warning system according to a second embodiment of the present invention. The embodiment of FIG. 2 is mostly the same as the embodiment of FIG. 1, the difference is that the facial feature comparison unit 15 and the processor 16 are directly provided on the ATM 10, eliminating the need for the ATM 10 to transfer data to the bank server host 20 via the network. time. Because the data transfer does not require a network connection, even if the network connection between the ATM 10 and the bank server host 20 fails, the early warning mechanism on the ATM 10 can still operate normally.
圖3係繪示本新型第一實施例的自動櫃員機預警方法的流程圖。如圖3所示，在步驟S10，以自動櫃員機10的讀取單元11判斷是否讀取到一金融卡帳號。若有讀取到金融卡帳號，則進入步驟S11。若沒有讀取到金融卡帳號，則結束預警方法。在步驟S11，當自動櫃員機10的讀取單元11讀取到金融卡帳號時，以讀取單元11輸出致能訊號至影像擷取元件12。由此可知，只有當金融卡***自動櫃員機10時，才能啟動影像擷取元件12。在步驟S12，以自動櫃員機10的影像擷取元件12連續地擷取多個臉部影像。在步驟S13，以臉部特徵比對單元21判斷該些臉部影像是否具有相同的臉部特徵，當臉部特徵比對單元21確認該些臉部影像具有相同的臉部特徵時，即表示自動櫃員機10的使用者為同一人，則接續執行步驟S14。反之，當該臉部特徵比對單元21確認該些臉部影像的臉部特徵不同時，即表示自動櫃員機10的使用者非同一人的情況，則結束預警方法。在步驟S14，以臉部特徵比對單元21輸出第一確認訊號至處理器22。在步驟S15時，當處理器22接收第一確認訊號後，以處理器22判斷該些臉部影像出現的總時間是否大於處理器22預設的時間上限。當處理器22確認總時間大於時間上限時，執行步驟S16。當處理器22確認總時間未大於時間上限時，即表示同一人在正常時間內操作自動櫃員機10的情況，則結束預警方法。在步驟S16，以處理器22輸出第二確認訊號至警示裝置13。在步驟S17，當自動櫃員機10的警示裝置13取得第二確認訊號後，以警示裝置13輸出警示訊號。在一實施例中，警示裝置13輸出的警示訊號將透過第一網路連接介面14傳送至保全中心，藉此呼叫保全中心的工作人員去處理。在另一實施例中，警示裝置13持續地輸出警示訊號，使得自動櫃員機10的使用者得以聽到警示訊號，直到讀取單元11讀不到金融卡帳號，警示裝置13才停止發出警示訊號。意即警示裝置13會不斷地警告自動櫃員機10的使用者，直到他停止使用金融卡操作自動櫃員機10為止。上述的安全預警機制，即是在模擬不肖人士採集停留於自動櫃員機10的按鍵上的指紋的情況、或者利用盜取的金融卡將現金轉帳至多個帳戶的情況。FIG. 3 is a flowchart illustrating an automatic teller machine early warning method according to the first embodiment of the present invention. As shown in FIG. 3, in step S10, the reading unit 11 of the ATM 10 determines whether a financial card account number is read. If a financial card account number is read, the process proceeds to step S11. If no financial card account number is read, the warning method is ended. In step S11, when the reading unit 11 of the ATM 10 reads the financial card account number, the reading unit 11 outputs an enable signal to the image capturing element 12. It can be seen that the image capturing element 12 can be activated only when the financial card is inserted into the ATM 10. In step S12, a plurality of facial images are continuously captured by the image capturing element 12 of the ATM 10. In step S13, the facial feature comparison unit 21 determines whether the facial images have the same facial features. When the facial feature comparison unit 21 confirms that the facial images have the same facial features, it means that If the user of the ATM 10 is the same person, step S14 is continuously performed. Conversely, when the facial feature comparison unit 21 confirms that the facial features of the facial images are different, it indicates that the users of the ATM 10 are not the same person, and the warning method is ended. In step S14, the facial feature comparison unit 21 outputs a first confirmation signal to the processor 22. In step S15, after the processor 22 receives the first confirmation signal, the processor 22 determines whether the total time of appearance of the facial images is greater than the time limit preset by the processor 22. When the processor 22 confirms that the total time is greater than the upper time limit, step S16 is executed. When the processor 22 confirms that the total time is not greater than the upper time limit, that is to say that the same person operates the ATM 10 within the normal time, then the warning method is ended. In step S16, the processor 22 outputs a second confirmation signal to the warning device 13. In step S17, when the warning device 13 of the ATM 10 obtains the second confirmation signal, the warning device 13 outputs a warning signal. In one embodiment, the warning signal output by the warning device 13 will be transmitted to the security center through the first network connection interface 14 to call the staff of the security center to process. In another embodiment, the warning device 13 continuously outputs a warning signal, so that the user of the ATM 10 can hear the warning signal, and the warning device 13 stops issuing the warning signal until the reading unit 11 cannot read the financial card account number. This means that the warning device 13 will continuously warn the user of the ATM 10 until he stops using the debit card to operate the ATM 10. The above-mentioned security early warning mechanism is to simulate a situation in which a bad person collects a fingerprint staying on a key of the ATM 10 or a case where a stolen financial card is used to transfer cash to multiple accounts.
圖4A及圖4B係繪示本新型第二實施例的自動櫃員機預警方法的流程圖。如圖4A及圖4B所示，步驟S20至步驟S27與圖3的步驟S10至步驟S17實質相同，圖4A及圖4B的實施例更包括步驟S28。當處理器22確認總時間未大於時間上限時，執行步驟S28。在步驟S28，以處理器22判斷在總時間內登入自動櫃員機10的相異帳號數量是否大於一數量門檻。當處理器22確認相異帳號數量大於數量門檻，即表示有不正常數量的金融卡持續登入自動櫃員機10，則執行步驟S26。當處理器22確認相異帳號數量未大於數量門檻，即表示登入自動櫃員機10的金融卡數量處於正常範圍，則結束預警方法。上述的預警機制，即是模擬不肖人士使用多張盜取的金融卡於自動櫃員機10進行交易的情況。FIG. 4A and FIG. 4B are flowcharts illustrating an early warning method of an ATM according to a second embodiment of the present invention. As shown in FIGS. 4A and 4B, steps S20 to S27 are substantially the same as steps S10 to S17 of FIG. 3, and the embodiment of FIGS. 4A and 4B further includes step S28. When the processor 22 confirms that the total time is not greater than the upper time limit, step S28 is executed. In step S28, the processor 22 determines whether the number of distinct account numbers logged into the ATM 10 within the total time is greater than a threshold. When the processor 22 confirms that the number of different account numbers is greater than the number threshold, it means that there are abnormal numbers of financial cards continuously logging in to the ATM 10, and step S26 is performed. When the processor 22 confirms that the number of different account numbers is not greater than the number threshold, it means that the number of financial cards logged into the ATM 10 is in a normal range, and the warning method is ended. The above-mentioned early-warning mechanism is to simulate a situation in which an unscrupulous person uses multiple stolen financial cards to conduct transactions on the ATM 10.
圖5A及圖5B係繪示本新型一實施例的自動櫃員機預警方法的流程圖。如圖5A及圖5B所示，步驟S30至步驟S38與圖4A及圖4B的步驟S20至步驟S28實質相同，圖5A及圖5B的實施例更包括步驟S39至步驟S42。當處理器22確認相異帳號數量未大於數量門檻時，則執行步驟S39。在步驟S39中，銀行伺服主機20儲存有一黑名單資料，該黑名單資料包含有多筆具有金融罪犯的臉部影像，以臉部特徵比對單元21判斷該些臉部影像是否符合黑名單資料內的臉部影像。若臉部特徵比對單元21確認該些臉部影像有符合黑名單資料內的臉部影像，則執行步驟S40。若臉部特徵比對單元21確認該些臉部影像沒有符合黑名單資料內的臉部影像，則結束預警方法。在步驟S40，以臉部特徵比對單元21發出第三確認訊號至處理器22。在步驟S41，當處理器22接收第三確認訊號後，以處理器22發出第四確認訊號至警示裝置13。在步驟S42中，當警示裝置13讀取第四確認訊號後，以警示裝置13發出警示訊號。上述的預警機制，即是加設一道關卡預防手法純熟的詐騙集團車手。5A and 5B are flowcharts illustrating an early warning method of an ATM according to an embodiment of the present invention. As shown in FIGS. 5A and 5B, steps S30 to S38 are substantially the same as steps S20 to S28 of FIGS. 4A and 4B. The embodiment of FIGS. 5A and 5B further includes steps S39 to S42. When the processor 22 confirms that the number of different account numbers is not greater than the number threshold, step S39 is performed. In step S39, the bank server host 20 stores a blacklist data. The blacklist data includes multiple facial images of financial criminals. The facial feature comparison unit 21 determines whether the facial images conform to the blacklist data. Face image inside. If the facial feature comparison unit 21 confirms that the facial images have facial images in the blacklist data, step S40 is performed. If the facial feature comparison unit 21 confirms that the facial images do not match the facial images in the blacklist data, the warning method is ended. In step S40, the facial feature comparison unit 21 sends a third confirmation signal to the processor 22. In step S41, after the processor 22 receives the third confirmation signal, the processor 22 sends a fourth confirmation signal to the warning device 13. In step S42, after the warning device 13 reads the fourth confirmation signal, the warning device 13 issues a warning signal. The above-mentioned early warning mechanism is to set up a checkpoint to prevent fraudulent group drivers who are skilled in tricks.
在其他實施例中，當警示裝置13發出警示訊號後， 銀行伺服主機20的處理器22更依據自動櫃員機10的所在地址，發出通知訊息給距離自動櫃員機10最近的警察局主機，藉此呼叫警察去自動櫃員機10進行處理。In other embodiments, when the warning device 13 sends out a warning signal, the processor 22 of the bank servo host 20 sends a notification message to the host of the police station closest to the ATM 10 according to the address of the ATM 10, thereby calling the police. Go to the ATM 10 for processing.
在其他實施例中，當自動櫃員機10的數量為多個時，以處理器14判斷是否相同的金融卡帳號登入不同位置的自動櫃員機10的總數量是否大於一數量上限。當不同位置的自動櫃員機10的總數量大於數量上限時，以處理器22發出第二確認訊號至金融卡目前登入的自動櫃員機10上的警示裝置13，藉以驅動警示裝置13發出警示訊號。上述的預警機制，即是在模擬不肖人士利用盜取的金融卡到多台自動櫃員機進行交易的情況。In other embodiments, when the number of ATMs 10 is multiple, the processor 14 determines whether the total number of ATMs 10 logged into different locations with the same financial card account number is greater than an upper limit. When the total number of ATMs 10 in different locations is greater than the upper limit, the processor 22 sends a second confirmation signal to the warning device 13 on the ATM 10 to which the financial card is currently logged in, thereby driving the warning device 13 to issue a warning signal. The above-mentioned early-warning mechanism is to simulate a situation in which an unscrupulous person uses a stolen financial card to conduct transactions at multiple ATMs.
本新型所提供的自動櫃員機預警系統，可以根據所偵測之臉部影像，判定自動櫃員機的操作人員是否為同一人。此外自動櫃員機更進一步紀錄金融卡登入自動櫃員機之總時間，藉此判定金融卡於自動櫃員機的登入時間是否異常。再者，更紀錄登入自動櫃員機的相異帳號數量，藉此判斷登入自動櫃員機的金融卡數量是否異常。透過多重預警機制之設定，提高處理器判斷是否發生金融盜領行為的正確機率，有效地減少誤判的次數，藉此避免警示裝置在錯誤的時機發出警示訊號，造成硬體資源的浪費。The automatic teller machine early warning system provided by the new model can determine whether the operator of the automatic teller machine is the same person based on the detected facial image. In addition, the ATM further records the total time for the financial card to log in to the ATM, thereby determining whether the login time of the financial card to the ATM is abnormal. Furthermore, the number of different accounts logged into the ATM is recorded to determine whether the number of financial cards logged into the ATM is abnormal. Through the setting of multiple early-warning mechanisms, the processor is able to increase the correct probability of judging whether financial theft occurs, effectively reducing the number of misjudgments, and thereby preventing the warning device from issuing warning signals at the wrong time, causing waste of hardware resources.
雖然本新型以前述之實施例揭露如上，然其並非用以限定本新型。在不脫離本新型之精神和範圍內，所為之更動與潤飾，均屬本新型之專利保護範圍。關於本新型所界定之保護範圍請參考所附之申請專利範圍。Although the present invention is disclosed as above with the foregoing embodiments, it is not intended to limit the present invention. Without departing from the spirit and scope of the new model, changes and retouching are within the scope of patent protection of the new model. For the protection scope defined by this new model, please refer to the attached patent application scope.
10‧‧‧自動櫃員機
11‧‧‧讀取元件
12‧‧‧影像擷取元件
13‧‧‧警示裝置
14‧‧‧第一網路連接介面
20‧‧‧銀行伺服主機
15、21‧‧‧臉部特徵擷取單元
16、22‧‧‧處理器
23‧‧‧第一網路連接介面
10‧‧‧ ATM
11‧‧‧Reading element
12‧‧‧Image capture element
13‧‧‧Warning device
14‧‧‧The first network connection interface
20‧‧‧Bank server host
15, 21‧‧‧Face feature extraction unit
16, 22‧‧‧ processor
23‧‧‧The first network connection interface
圖1係繪示本新型第一實施例的自動櫃員機預警系統的示意圖。
圖2係繪示本新型第二實施例的自動櫃員機預警系統的示意圖。
圖3係繪示本新型第一實施例的自動櫃員機預警方法的流程圖。
圖4A及圖4B係繪示本新型第二實施例的自動櫃員機預警方法的流程圖。
圖5A及圖5B係繪示本新型第三實施例的自動櫃員機預警方法的流程圖。
FIG. 1 is a schematic diagram illustrating an automatic teller machine early warning system according to a first embodiment of the present invention.
FIG. 2 is a schematic diagram illustrating an automatic teller machine early warning system according to a second embodiment of the present invention.
FIG. 3 is a flowchart illustrating an automatic teller machine early warning method according to the first embodiment of the present invention.
FIG. 4A and FIG. 4B are flowcharts illustrating an early warning method of an ATM according to a second embodiment of the present invention.
FIG. 5A and FIG. 5B are flowcharts illustrating an early warning method of an ATM according to a third embodiment of the present invention.
Claims (6)
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