3d Image Processing Robot

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Abstract: For an 3D IMAGE PROCESSING robot to truly succeed, there must be a variety of ways for robot to interpret its surrounding environment, both quickly and accurately. This report focuses on investigating improvements for a sub- problem of environmental perception, namely 3D image processing, referring to localizing and classifying objects of interests in a specified environment. The objects of interests in a process security scan of baggage or to analyse scans of materials to understand their structure. Recently python3 & machine learning programming approaches have made significant progress in the field of 3d object detection. Thus, several techniques have been developed for the real time tasks such as the autonomous robot. However, as images lack some information about depth which is essential for environmental perception for autonomous robot, they struggle a lot to preserve distance between object and robot. So, in this project in order to avoid such delays we have used high quality camera OF 1080p. This Report investigates the performance of both the minicomputers and as well as the cameras being mounted on the robot for 3d analysis which uses the state-of-the-3d image processing models. The end-to-end models of python3 and OpenCV are ultimately performed and experimented various times to perform 3D Detections. The models were trained and evaluated on the recently released data set and the most promising model was able to detect the 3d image of the object