{"references": ["Patel, R., Sanghavi, S., Gupta, D., & Raval, M. S. (2015, November). CheckIt-A low cost mobile OMR system. In TENCON 2015-2015 IEEE Region 10 Conference (pp. 1-5). IEEE.", "Karunanayake, N. (2015). OMR sheet evaluation by web camera using template matching approach. International Journal for Research in Emerging Science and Technology, 2(8)", "Kakade N. Omr Sheet Evaluation using Image Processing. JETIR.", "Deng, H., Wang, F., & Liang, B. (2008, December). A low-cost OMR solution for educational applications. In 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications (pp. 967-970). IEEE.", "Atal, R., Arora, A. International journal of Computer science and Artificial Intelligence.3(2).", "Dejan, G., Nikola, G., & Dragan, M. (2000). A simple system for automatic exam scoring using optical markup reader. In Second Balkan IFAC International Symposium (pp. 149- 153).", "Chinnasarn, K., & Rangsanseri, Y. (1999, October). Image-processingoriented optical mark reader. In Applications of digital image processing XXII (Vol. 3808, pp. 702- 708). International Society for Optics and Photonics.", "Singh, T. R., Roy, S., Singh, O. I., Sinam, T., & Singh, K. (2012). A new local adaptive thresholding technique in binarization. arXiv preprint arXiv:1201.5227.", "Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on pattern analysis and machine intelligence, (6), 679-698.", "Rajasekaran, A., & Senthilkumar, P. (2014). Image denoising using median filter with edge detection using canny operator."]}

Optical imprint acknowledgment is the method involved with distinguishing presence or nonattendance of an imprint in a foreordained position. OMR is currently utilized as an info gadget for information section. Examining OMR sheets is normally done by a scanner. This project aims to overcome the use of scanners to scan OMR sheets by using a smartphone to capture the image of the sheet and send it to the server which will process the image and find the marked zones compare values, then check with input key and show the total. The data is then stored in the MongoDb. This project will utilize the availability of smartphones with almost everyone to make this process simpler by dividing the task into smaller tasks among the assigned faculty. Further with smartphones coming with better cameras we can get very accurate results than before. Also the project is implemented in flutter using dart so the app can be used for IoS also. The app is lightweight as the processing is done in the back-end. The project is an innovation on how to use new technological advancements in an innovative way to solve problems at their simplest level thereby reducing overall complexity of the system. The results are stored in JSON format.