Abstract: Computer vision makes extensive use of object detection. and crucial for variety of applications, by identifying and locating objects in images and videos. It’s a crucial technology for many applications, like self-driving cars and facial recognition. In general when objects are exposed to light then object detection can be done by using simple weights algorithm like Mobile Weight algorithm (MW) of object detection and identification and Common Objects In Context (COCO) data set. In MW algorithm the binary Images this used for comparison can’t accept larger variation of objects and it have faults in algorithm so we utilized You Only Live Once Algorithm (YOLO).It is used most frequency in variety of application by charity of image or video is required so updated Algorithm need to be used for increasing the efficiency of system so that object detection and identification in even in front view and top view of images or in video. Finally, Using the Machine learning approach we are trying to improve the accuracy of the classification tasks. More or less we are expecting 0.88 weighted average precision, 0.74 weighted average recall,
0.80 weighted average f1-score, and 90.51 percent accuracy by the proposed Machine Learning and computer vision methods.
Keywords: Computer Vision Method, Image processing, Coco data set, Mobile Weight algorithm, Classification and detection, You Only Live Once algorithm.
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DOI:
10.17148/IJARCCE.2024.134180
