The Application Of Contour Recognition In The Self-Study Space Locating System

Nowadays,almost every classroom in universities install the monitoring camera,which makes it possible for college students to obtain the information of self-study rooms using video technology.In order to solve the problems of limited self-study room resources,the difficulties of college students in finding a private study room,and the unequal distribution of self-study room resources,this thesis adapts contour recognition technology to detect the number of college study rooms,and uses the Web to design a Web APP including all the information of the self-study room,with which is more easy for college students to research the available self-study rooms and also improve the using rate of college study rooms.And the main work of the thesis is reflected in the following three points.Firstly,the thesis chooses self-study rooms as research object.After the empirical study of existing information systems and college students,the needs of system users is ascertained and then use the unified modeling language to define the software requirements of the system.These needs include the frequency of using self-study rooms,the opening hour and user's feedback.And then the system based on the needs of users does some requirement analysis and further describe its functional requirements.Besides,the detection process of the system's function structure and contour recognition technology is designed.Secondly,the system takes advantage of contour recognition to recognize if there are students in study rooms.At first,the self-study room image is obtained and be preprocessed through the university logistics system.The image preprocessing is divided into three steps: removing interference information,banalization,and morphological processing so as to get the candidate area of the head preliminarily.Next,supposing the maximum and minimum area of study room,the candidate area is calculated.Compared with the set threshold,the possibility that the candidate area is not within the area threshold is excluded.Then,Setting the circularity threshold,the circularity of the candidate region is calculated,which is within the value range is head.Finally,counting the final number of the head areas,the occupancy rate of each study room is calculated and the system vacancy query module is simulated.The experimental results show that the head detection method based on contour can detect the number of self-study rooms effectively on condition of the human head being severely obstructed.And comparing the empirical data with the actual number of students in study rooms,it indicates the same result.Therefore,what shows that the head detection method based on contour can detect the number of self-study rooms effectively,which provides a powerful guarantee for developing the seat inquiry system of self-study room in the next step.Thirdly,the paper adopts B/S framework,uses web development technology to develop the self-study room vacancy inquiry system,uses the HTML5 language to develop the system client and the PHP language to develop the system background,and selects MySQL database as the database of the system.Through the analysis of collect data with the college monitoring system,it shows that the self-study room vacancy inquiry system meets the requirements of original users as its accuracy is more than 80%.