TWM469556U - Intelligent monitoring device for perform face recognition in cloud - Google Patents
Intelligent monitoring device for perform face recognition in cloud Download PDFInfo
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本創作係有關於一種以雲端進行人臉偵測之智慧監視裝置，尤其是指一種分散式運算平台Ｈａｄｏｏｐ來實現人臉偵測及影像的快速處理，且令監控者可以透過網際網路隨時隨地得到監控資訊的裝置。This creative department is about a smart surveillance device for face detection in the cloud, especially a distributed computing platform Hadoop for face detection and image processing, and allows the monitor to access the Internet anytime, anywhere. A device that receives monitoring information.
傳統的監視系統，均是透過監控者坐在監控端前面盯著監控螢幕來達到監視的效果。然而，一般人類眼睛集中注意力的時間大約是２０分鐘，因此當監控者的眼睛不停的注視監控端螢幕超過２０分鐘後，很有可能會造成就算有可疑人物或不明車輛或物體進入監控螢幕，也不會去注意到，造成監控的漏洞。基於此一情形，智慧型監視系統的研究也開始逐漸興起，如文獻１「蔡博智，影像追蹤方法應用在監控系統之研究，中原大學機械工程學系碩士論文，民國９１」，其係以移動目標平移法與移動邊緣檢測法對物體作追蹤，但此方法只要移動物體就會去進行追蹤，非常容易發生錯誤；對此，文獻２「黃敏峰，人臉追蹤法應用於監視系統之研究，成功大學電機工程學系，碩士論文，民國９２年」即進一步利用膚色去辨識出可能為人臉的區域，以得到較佳的監視效果，又如我國專利公告編號M432892「人臉偵測辨識裝置」，主要揭示一種包括選擇模組、過濾模組、區塊模組以及標定模組之人臉辨識裝置。The traditional monitoring system is to monitor the screen by the monitor sitting in front of the monitoring terminal to achieve the monitoring effect. However, the average human eye is focused for about 20 minutes, so when the monitor's eyes keep watching the monitor screen for more than 20 minutes, it is likely that even if there are suspicious people or unknown vehicles or objects entering the monitor screen. And will not notice, causing loopholes in monitoring. Based on this situation, the research of intelligent surveillance systems has begun to emerge, such as the literature 1 "Cai Bozhi, the application of image tracking methods in the monitoring system, the master of mechanical engineering at Zhongyuan University, the Republic of China, the Republic of China 91", which is based on mobile targets. The translation method and the moving edge detection method track the object, but this method is very easy to make mistakes as long as the object is moved. In this regard, Document 2 "Huang Minfeng, face tracking method applied to surveillance system research, successful university Department of Electrical Engineering, Master's thesis, the Republic of China in 1992, is to further use the skin color to identify areas that may be human faces, in order to obtain better monitoring results, such as the Chinese Patent Bulletin No. M432892 "Face Detection and Identification Device". A face recognition device including a selection module, a filter module, a block module, and a calibration module is mainly disclosed.
近幾年來，人臉偵測的方法不斷更新進步，使得人臉偵測及追蹤的應用逐漸廣泛，例如監視系統、保全系統、人臉辨識系統等等…都是透過人臉偵測等技術的應用範圍。然而，目前市面上所出現的人臉辨識系統，大多是一套系統就必須搭配一台運算主機，例如機場人臉辨識系統、保險箱人臉辨識系統等等…都是各自需要一台主機運作，因此造成同一政府機關或事業體在越多地方設置人臉辨識系統，則該政府機關或事業體所需要的設置成本也會相對提高。In recent years, the method of face detection has been continuously updated, making the application of face detection and tracking more and more widely, such as surveillance systems, security systems, face recognition systems, etc., all through the face detection and other technologies. Application range. However, most of the face recognition systems currently on the market must be equipped with a computing host, such as an airport face recognition system, a safe face recognition system, etc., each of which requires a host to operate. As a result, the number of face recognition systems installed in the same government agency or business unit will increase the installation cost of the government agency or business.
本創作之主要目的，係提供一種以雲端進行人臉偵測之智慧監視裝置，其係利用分散式運算平台Ｈａｄｏｏｐ來實現雲端人臉偵測及快速的影像處理，再利用其運算結果結合網際網路，使得監控者可以透過網頁，隨時隨地得到監控的結果等資訊，達到雲端服務的目的。The main purpose of this creation is to provide a smart surveillance device for face detection in the cloud, which uses the distributed computing platform Hadoop to implement cloud face detection and fast image processing, and then use the results of the operation in conjunction with the Internet. The road enables the monitor to obtain the monitoring results and other information anytime and anywhere through the webpage to achieve the purpose of the cloud service.
上述本創作之主要目的與功效，是由以下之具體技術手段所達成：The main purpose and effect of the above creations are achieved by the following specific technical means:
一種以雲端進行人臉偵測之智慧監視裝置，係包括至少一影像擷取單元、一雲端影像處理單元以及至少一網路監看單元；其中：A smart monitoring device for detecting a face in the cloud includes at least one image capturing unit, a cloud image processing unit, and at least one network monitoring unit; wherein:
該影像擷取單元，包括一影像擷取模組，用以將影像訊號轉換成影像檔案；一影像擷取命令控制模組，連接至該影像擷取模組，負責維護目前已經擷取到的影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］，並連結至該雲端影像處理單元，以透過事件驅動的方式達成訊息的交換；一影像傳輸模組，連接至該影像擷取命令控制模組，係執行該影像擷取命令控制模組所下達的控制命令，將影像檔案傳送到該雲端影像處理單元；The image capturing unit includes an image capturing module for converting the image signal into an image file, and an image capturing command control module connected to the image capturing module for maintaining the currently captured image. The image file list [FIFO Queue] is connected to the cloud image processing unit to exchange information through an event-driven manner; an image transmission module is connected to the image capture command control module to execute the image. Taking the control command issued by the command control module, and transmitting the image file to the cloud image processing unit;
該雲端影像處理單元，包括一雲端影像命令控制模組，對應於該影像擷取命令控制模組，以接受由該影像擷取命令控制模組要求處理影像的控制命令；一影像接收模組，相對於影像傳輸模組，並連接該雲端影像命令控制模組，係當收到該雲端影像命令控制模組的命令後接收該影像傳輸模組所傳送過來的影像；一Ｈａｄｏｏｐ分散式影像處理模組，連接至該雲端影像命令控制模組，負責執行影像處理及人臉偵測辨識的工作；一Ｈａｄｏｏｐ檔案資料庫，分別連接至該影像接收模組及該Ｈａｄｏｏｐ分散式影像處理模組，用以存放該影像接收模組所接收之影像檔案及經該Ｈａｄｏｏｐ分散式影像處理模組處理、分析後的影像檔案；The cloud image processing unit includes a cloud image command control module corresponding to the image capture command control module to receive a control command required by the image capture command control module to process an image; an image receiving module, The image transmission module is connected to the cloud image command control module, and receives the image transmitted by the image transmission module after receiving the command of the cloud image command control module; a Hadoop distributed image processing module The group is connected to the cloud image command control module and is responsible for performing image processing and face detection and identification; a Hadoop file database is respectively connected to the image receiving module and the Hadoop distributed image processing module, The image file received by the image receiving module and the image file processed and analyzed by the Hadoop distributed image processing module are stored;
該網路監看單元，係提供監看人員進入Ｈａｄｏｏｐ檔案資料庫中查看人臉偵測結果。The network monitoring unit provides monitoring personnel to enter the Hadoop file database to view the face detection results.
如上所述之人臉偵測之雲端智慧監視系統，其中，該影像擷取模組為一鏡頭可以進行左右轉動（Ｐａｎ）、上下傾斜（Ｔｉｌｅ）與放大（Ｚｏｏｍ）功能之攝影機。The cloud smart monitoring system for face detection as described above, wherein the image capturing module is a camera capable of performing a left and right rotation (Pan), up and down tilt (Zile) and zoom (Zoom) functions.
如上所述之人臉偵測之雲端智慧監視系統，其中，該Ｈａｄｏｏｐ分散式影像處理模組所述的影像處理為經一連串的彩色影像轉灰階影像、低通濾波、邊緣檢測、二值化及外形影像運算之處理流程。The cloud smart monitoring system for face detection as described above, wherein the image processing of the Hadoop distributed image processing module is a series of color image grayscale images, low pass filtering, edge detection, binarization And the processing flow of the shape image operation.
如上所述之以雲端進行人臉偵測之智慧監視裝置，其中，該影像擷取模組為一鏡頭可以進行左右轉動（Ｐａｎ）、上下傾斜（Ｔｉｌｅ）與放大（Ｚｏｏｍ）功能之攝影機。The smart monitoring device for performing face detection in the cloud as described above, wherein the image capturing module is a camera capable of performing a left and right rotation (Pan), up and down tilt (Zile) and zoom (Zoom) functions.
如上所述之以雲端進行人臉偵測之智慧監視裝置，其中，該Ｈａｄｏｏｐ分散式影像處理模組所述的影像處理為經一連串的彩色影像轉灰階影像、低通濾波、邊緣檢測、二值化及外形影像運算之處理流程。The smart monitoring device for performing face detection in the cloud as described above, wherein the image processing of the Hadoop distributed image processing module is a series of color image grayscale images, low pass filtering, edge detection, and second The processing flow of value and shape image operations.
如上所述之以雲端進行人臉偵測之智慧監視裝置，其中，該Ｈａｄｏｏｐ分散式影像處理模組係運用膚色偵測、橢圓遮罩比對、嘴唇偵測及眼睛偵測運算法進行人臉偵測辨識。The smart monitoring device for face detection in the cloud as described above, wherein the Hadoop distributed image processing module performs face detection using skin color detection, elliptical mask matching, lip detection and eye detection algorithms. Detection identification.
如上所述之以雲端進行人臉偵測之智慧監視裝置，其中，該Ｈａｄｏｏｐ檔案資料庫包括一儲存由該影像接收模組所接收之影像資料檔案的影像索引儲存區，以及一經人臉辨識後確定為人臉影像之人臉偵測結果儲存區。The smart monitoring device for performing face detection in the cloud as described above, wherein the Hadoop file database includes an image index storage area for storing image data files received by the image receiving module, and after face recognition The face detection result storage area determined as a face image.
本創作之優點在於：The advantages of this creation are:
本創作之以雲端進行人臉偵測之智慧監視裝置，可以運用於需要大量監控設備的場所或公司，結合網路的方式，使得人們可以不用一直盯著監視器畫面，隨時隨地透過網路監看單元查看監視畫面，並且做出相對因應的措施；同時，因人臉的辨識作業是在雲端進行，因此在不同的場合並不需要另外各自配置人臉辨識系統，僅需架設影像擷取單元並將其所結取的影像檔案傳送至雲端處理即可，而能夠大幅降低人臉辨識系統設置的成本。The smart monitoring device for face detection in the cloud can be applied to places or companies that need a large number of monitoring devices. The way of combining the network allows people to keep watching the monitor screen and monitor the network anytime, anywhere. The unit looks at the monitoring screen and makes corresponding measures. At the same time, since the face recognition operation is performed in the cloud, it is not necessary to separately configure the face recognition system in different occasions, and only the image capturing unit needs to be set up. The image files obtained by the images are transmitted to the cloud for processing, and the cost of the face recognition system setting can be greatly reduced.
（１）‧‧‧影像擷取單元(1)‧‧‧Image capture unit
（１１）‧‧‧影像擷取模組(11)‧‧‧Image capture module
（１２）‧‧‧影像擷取命令控制模組(12)‧‧‧Image capture command control module
（１３）‧‧‧影像傳輸模組(13)‧‧‧Image transmission module
（２）‧‧‧雲端影像處理單元(2) ‧‧‧Cloud Image Processing Unit
（２１）‧‧‧雲端影像命令控制模組(21)‧‧‧Cloud Image Command Control Module
（２２）‧‧‧影像接收模組(22)‧‧‧Image receiving module
（２３）‧‧‧Ｈａｄｏｏｐ分散式影像處理模組(23)‧‧‧Hadoop Decentralized Image Processing Module
（２４）‧‧‧Ｈａｄｏｏｐ檔案資料庫(24) ‧‧‧Hadoop archive database
（３）‧‧‧網路監看單元(3) ‧‧‧Network Monitoring Unit
第一圖：本創作以雲端進行人臉偵測之智慧監視裝置其一較佳實施例的方塊架構圖The first figure: a block diagram of a preferred embodiment of the smart monitoring device for face detection in the cloud
第二圖：本創作以雲端進行人臉偵測之智慧監視裝置其二較佳實施例的方塊架構圖The second figure: the block diagram of the second preferred embodiment of the smart monitoring device for face detection in the cloud
為令本創作之技術手段、創作目的及達成功效有更完整及清楚的揭露，茲於下詳細說明之，並請一併參閱揭示之圖式及元件符號。In order to make the technical means, creative purpose and achievement of this creation more complete and clear, it is explained in detail below, and please refer to the disclosed drawings and component symbols.
請參看第一圖，為本創作之以雲端進行人臉偵測之智慧監視裝置的方塊架構圖。在第一圖中所揭示之較佳實施例中，本創作以雲端進行人臉偵測之智慧監視裝置係包括：一影像擷取單元（１）以及一雲端影像處理單元（２）；其中：Please refer to the first figure for the block diagram of the smart monitoring device for face detection in the cloud. In the preferred embodiment disclosed in the first figure, the smart monitoring device for performing face detection in the cloud includes: an image capturing unit (1) and a cloud image processing unit (2); wherein:
該影像擷取單元（１）包括一影像擷取模組（１１）、一影像擷取命令控制模組（１２）以及一影像傳輸模組（１３），該影像擷取模組（１１）連接至該影像擷取命令控制模組（１２），該影像擷取命令控制模組（１２）再連接至該影像傳輸模組（１３）。The image capturing unit (1) includes an image capturing module (11), an image capturing command control module (12), and an image transmission module (13). The image capturing module (11) is connected. The image capture command control module (12) is connected to the image capture module (13).
該影像擷取模組（１１），係作為影像擷取之用，並將影像訊號資料轉換為影像檔案；在本實施例中該影像擷取模組（１１）為一鏡頭可以進行左右轉動（Ｐａｎ）、上下傾斜（Ｔｉｌｅ）與放大（Ｚｏｏｍ）功能之攝影機。The image capturing module (11) is used for image capturing, and converts the image signal data into an image file. In this embodiment, the image capturing module (11) can rotate left and right for a lens ( Pan), camera with up and down tilt and zoom functions.
該影像擷取命令控制模組（１２），為該影像擷取單元（１）的控制核心。當該影像擷取模組（１１）擷取影像並轉換為影像檔案後，會將影像檔案存放至該影像擷取命令控制模組（１２）的影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］中，以由該影像擷取命令控制模組（１２）負責維護存放在該影像檔案列表中之影像檔案的傳送時機與順序；且當影像檔案傳送到雲端影像處理單元（２）後，並下達影像檔案已傳送完成命令；這些動作為多執行緒同步工作，係透過事件驅動的方式達成訊息的交換。The image capture command control module (12) is a control core of the image capture unit (1). After the image capturing module (11) captures the image and converts it into an image file, the image file is stored in the image file list [FIFO Queue] of the image capturing command control module (12). The image capture command control module (12) is responsible for maintaining the transmission timing and sequence of the image files stored in the image file list; and when the image file is transmitted to the cloud image processing unit (2), the release image file has been transferred. Commands; these actions are multi-thread synchronization work, which is an event-driven exchange of messages.
該影像傳輸模組（１３），其是透過持續監聽影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］來確認是否有來自該影像擷取命令控制模組（１２）所下達的控制命令，如果影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］不是空的，該影像傳輸模組（１３）會將影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］裡所指定的影像資料檔案傳送到該雲端影像處理單元（２），該雲端影像處理單元（２）會有相對應的影像接收模組（２２）接收上傳之影像資料檔案；如果影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］是空的，該影像傳輸模組（１３）將處於等待狀態。The image transmission module (13) is configured to continuously check the image file list [FIFO Queue] to confirm whether there is a control command from the image capture command control module (12), if the image file list [FIFO Queue] ] is not empty, the image transmission module (13) will transmit the image data file specified in the image file list [FIFO Queue] to the cloud image processing unit (2), and the cloud image processing unit (2) will have The corresponding image receiving module (22) receives the uploaded image data file; if the image file list [FIFO Queue] is empty, the image transmission module (13) will be in a waiting state.
該雲端影像處理單元（２），包括一雲端影像命令控制模組（２１）、一影像接收模組（２２）、一Ｈａｄｏｏｐ分散式影像處理模組（２３）及一Ｈａｄｏｏｐ檔案資料庫（２４）；該雲端影像命令控制模組（２１）分別連接至該影像接收模組（２２）及該Ｈａｄｏｏｐ分散式影像處理模組（２３），又該Ｈａｄｏｏｐ檔案資料庫（２４）分別與該影像接收模組（２２）、該Ｈａｄｏｏｐ分散式影像處理模組（２３）連接。The cloud image processing unit (2) includes a cloud image command control module (21), an image receiving module (22), a Hadoop distributed image processing module (23), and a Hadoop file database (24). The cloud image command control module (21) is respectively connected to the image receiving module (22) and the Hadoop distributed image processing module (23), and the Hadoop file database (24) and the image receiving module respectively The group (22) and the Hadoop distributed image processing module (23) are connected.
該雲端影像命令控制模組（２１），係相對於該影像擷取單元（１）的影像擷取命令控制模組（１２），用以做為雙方交換訊息之用。當有來自影像擷取單元（１）要求處理影像資料的控制命令，並為該雲端影像命令控制模組（２１）接收時，該雲端影像命令控制模組（２１）除了通知該影像接收模組（２２）接收影像資料檔案之外，同時會觸發該Ｈａｄｏｏｐ分散式影像處理模組（２３）進行處理影像資料檔案。The cloud image command control module (21) is an image capture command control module (12) relative to the image capture unit (1) for use as a message exchange between the two parties. The cloud image command control module (21) notifies the image receiving module when there is a control command from the image capturing unit (1) to process the image data and is received by the cloud image command control module (21). (22) In addition to receiving the image data file, the Hadoop distributed image processing module (23) is triggered to process the image data file.
該影像接收模組（２２），係接收來自影像擷取單元（１）之影像傳輸模組（１３）上傳之影像資料檔案，並將接收後的影像資料檔案存放至該Ｈａｄｏｏｐ檔案資料庫（２４），並更新位於Ｈａｄｏｏｐ檔案資料庫（２４）中的影像索引檔。The image receiving module (22) receives the image data file uploaded from the image transmission module (13) of the image capturing unit (1), and stores the received image data file in the Hadoop file database (24). ) and update the image index file located in the Hadoop archive database (24).
該Ｈａｄｏｏｐ分散式影像處理模組（２３），係當該雲端影像命令控制模組（２１）通知該Ｈａｄｏｏｐ分散式影像處理模組（２３）需要處理影像檔資料時，該Ｈａｄｏｏｐ分散式影像處理模組（２３）便會至Ｈａｄｏｏｐ檔案資料庫（２４）中擷取需要處理的影像檔案，於經一連串的彩色影像轉灰階影像、低通濾波、邊緣檢測、二值化、外形影像運算等影像處理後，再進行人臉偵測運算，該人臉偵測運算係運用膚色偵測、橢圓遮罩比對、嘴唇偵測及眼睛偵測運算法，於判斷為人臉影像後，將該辨識後的人臉影像檔案存回該Ｈａｄｏｏｐ檔案資料庫（２４）中。The Hadoop distributed image processing module (23) is a Hadoop distributed image processing module when the cloud image command control module (21) notifies the Hadoop distributed image processing module (23) that the image file data needs to be processed. The group (23) will go to the Hadoop file database (24) to retrieve the image files to be processed, and then through a series of color images to grayscale images, low-pass filtering, edge detection, binarization, shape image operations and other images. After the processing, the face detection operation is performed. The face detection operation uses the skin color detection, the ellipse mask comparison, the lip detection and the eye detection algorithm to determine the face image. The subsequent face image file is stored back in the Hadoop archive database (24).
該Ｈａｄｏｏｐ檔案資料庫（２４），其分為二部分，其一係儲存由該影像接收模組（２２）所接收之影像資料檔案的影像索引儲存區，另一為經人臉辨識後確定為人臉影像之人臉偵測結果儲存區。The Hadoop file database (24) is divided into two parts, one of which stores an image index storage area of the image data file received by the image receiving module (22), and the other is determined by face recognition. The face detection result storage area of the face image.
據此，透過該影像擷取模組（１１）擷取影像，並將擷取的影像訊號資料轉換成影像檔案，且存放於該影像擷取命令控制模組（１２）中，接著該影像擷取命令控制模組（１２）下達傳送影像資料檔案命令給該影像傳輸模組（１３）與雲端影像命令控制模組（２１），該雲端影像命令控制模組（２１）便會通知該影像接收模組（２２）準備接收影像資料檔案，並告知該Ｈａｄｏｏｐ分散式影像處理模組（２３）須準備進行影像的辨識；當該影像傳輸模組（１３）接收到該影像擷取命令控制模組（１２）開始傳送影像資料檔案的訊息後，該影像擷取模組（１１）便會將該些儲存於影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］的影像檔傳資料送出去，而由雲端影像處理單元（２）之影像接收模組（２２）接收，接收後的影像資料檔案會被指定存放在該Ｈａｄｏｏｐ檔案資料庫（２４）之影像檔案索引區中，此時該Ｈａｄｏｏｐ分散式影像處理模組（２３）即能到該Ｈａｄｏｏｐ檔案資料庫（２４）之影像檔案索引區中取出所需影像資料檔案進行人臉偵測分析，並在完成人臉偵測分析後將處理後的影像資料檔案儲存於該Ｈａｄｏｏｐ檔案資料庫（２４）之人臉偵測結果儲存區中，如此監看人員便能透過網路監看單元（３）進入Ｈａｄｏｏｐ檔案資料庫（２４）之人臉偵測結果儲存區中隨時隨地監看人臉偵測結果。Accordingly, the image capture module (11) captures the image, and the captured image signal data is converted into an image file, and is stored in the image capture command control module (12), and then the image is The command control module (12) sends a command to transmit the image data file to the image transmission module (13) and the cloud image command control module (21), and the cloud image command control module (21) notifies the image receiving The module (22) is ready to receive the image data file, and informs the Hadoop distributed image processing module (23) that the image recognition module is ready to perform image recognition; when the image transmission module (13) receives the image capture command control module (12) After the message of the image data file is started, the image capturing module (11) sends the image file stored in the image file list [FIFO Queue], and the cloud image processing unit ( 2) The image receiving module (22) receives, and the received image data file is designated to be stored in the In the image file index area of the adoop file database (24), the Hadoop distributed image processing module (23) can retrieve the desired image data file from the image file index area of the Hadoop file database (24). Performing face detection analysis and storing the processed image data files in the face detection result storage area of the Hadoop file database (24) after the face detection analysis is completed, so that the monitoring personnel can The network monitoring unit (3) enters the face detection result storage area of the Hadoop file database (24) to monitor the face detection result anytime and anywhere.
請參看第二圖，其係本創作之另一較佳實施例，其與第一圖所揭示之實施例之主要差異是在：本實施例架設了數多個影像擷取單元（１），且該些影像擷取單元（１）均將所擷取的影像傳送至該雲端影像處理單元（２）進行人臉偵測辨識處理，同時監測者能隨時透過不同的網路監看單元（３）到雲端查看人臉偵測辨識結果，達到隨時監看之效果。Please refer to the second figure, which is another preferred embodiment of the present invention. The main difference between the embodiment and the embodiment disclosed in the first figure is that: the embodiment has several image capturing units (1) installed. The image capturing unit (1) transmits the captured image to the cloud image processing unit (2) for face detection and identification processing, and the monitor can access the network monitoring unit at any time (3) ) View the face detection and identification results in the cloud to achieve the effect of monitoring at any time.
以上所舉者僅係本創作之部份實施例，並非用以限制本創作，致依本創作之創意精神及特徵，稍加變化修飾而成者，亦應包括在本專利範圍之內。The above are only some of the examples of this creation, and are not intended to limit the creation of this creation. It should be included in the scope of this patent, based on the creative spirit and characteristics of this creation.
綜上所述，本創作實施例確能達到所預期之使用功效，又其所揭露之具體構造，不僅未曾見諸於同類產品中，亦未曾公開於申請前，誠已完全符合專利法之規定與要求，爰依法提出新型專利之申請，懇請惠予審查，並賜准專利，則實感德便。In summary, the present embodiment can achieve the expected use efficiency, and the specific structure disclosed therein has not been seen in similar products, nor has it been disclosed before the application, and has fully complied with the provisions of the Patent Law. And the request, the application for a new type of patent in accordance with the law, please forgive the review, and grant the patent, it is really sensible.
(1)‧‧‧影像擷取單元 (1)‧‧‧Image capture unit
(11)‧‧‧影像擷取模組 (11)‧‧‧Image capture module
(12)‧‧‧影像擷取命令控制模組 (12)‧‧‧Image capture command control module
(13)‧‧‧影像傳輸模組 (13)‧‧‧Image transmission module
(2)‧‧‧雲端影像處理單元 (2) ‧‧‧Cloud Image Processing Unit
(21)‧‧‧雲端影像命令控制模組 (21)‧‧‧Cloud Image Command Control Module
(22)‧‧‧影像接收模組 (22)‧‧‧Image receiving module
(23)‧‧‧Hadoop分散式影像處理模組 (23)‧‧‧Hadoop Decentralized Image Processing Module
(24)‧‧‧Hadoop檔案資料庫 (24) ‧‧‧Hadoop archive database
(3)‧‧‧網路監看單元 (3) ‧‧‧Network Monitoring Unit
Claims (8)
該影像擷取單元，包括一影像擷取模組，用以將影像訊號轉換成原始影像檔案；一影像擷取命令控制模組，連接至該影像擷取模組，負責維護目前已經擷取到的影像檔案列表［ＦＩＦＯ Ｑｕｅｕｅ］，並連結至該雲端影像處理單元，以透過事件驅動的方式達成訊息的交換；一影像傳輸模組，執行該影像擷取命令控制模組所下達的控制命令，將影像檔案傳送到該雲端影像處理單元；
該雲端影像處理單元，包括一雲端影像命令控制模組，對應於該影像擷取命令控制模組，以接受由該影像擷取命令控制模組要求處理影像的控制命令；一影像接收模組，相對於該影像傳輸模組，做為接收來自該影像傳輸模組所傳送過來的影像；一Ｈａｄｏｏｐ分散式影像處理模組，連接至該雲端影像命令控制模組，負責執行影像處理及人臉偵測辨識的工作；一Ｈａｄｏｏｐ檔案資料庫，分別連接至該影像接收模組及該Ｈａｄｏｏｐ分散式影像處理模組，用以存放影像檔案及影像分析的結果；
該網路監看單元，係提供監看人員進入該Ｈａｄｏｏｐ檔案資料庫中查看人臉偵測結果。A smart monitoring device for detecting a face in the cloud includes at least one image capturing unit, a cloud image processing unit, and at least one network monitoring unit; wherein:
The image capturing unit includes an image capturing module for converting the image signal into the original image file; an image capturing command control module is connected to the image capturing module, and the maintenance is currently captured. The image file list [FIFO Queue] is connected to the cloud image processing unit to exchange information through an event-driven manner; an image transmission module executes a control command issued by the image capture command control module, Transfer the image file to the cloud image processing unit;
The cloud image processing unit includes a cloud image command control module corresponding to the image capture command control module to receive a control command required by the image capture command control module to process an image; an image receiving module, Relative to the image transmission module, as receiving the image transmitted from the image transmission module; a Hadoop distributed image processing module is connected to the cloud image command control module, and is responsible for performing image processing and face detection The identification work is performed; a Hadoop file database is respectively connected to the image receiving module and the Hadoop distributed image processing module for storing image file and image analysis results;
The network monitoring unit provides the monitoring personnel to enter the Hadoop file database to view the face detection result.
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| TWI512641B (en) * | 2014-04-02 | 2015-12-11 | Pegatron Corp | Identification system and identification method |
| TWI740624B (en) * | 2019-10-28 | 2021-09-21 | 中國商深圳市商湯科技有限公司 | Image processing method, device and storage medium |
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| TWI512641B (en) * | 2014-04-02 | 2015-12-11 | Pegatron Corp | Identification system and identification method |
| TWI740624B (en) * | 2019-10-28 | 2021-09-21 | 中國商深圳市商湯科技有限公司 | Image processing method, device and storage medium |
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