Stereo vision is the process which is similar to the human being vision i.e. stereopsis. As we all know that stereo vision is field of computer vision and this is related to artificial intelligence field the stereo vision can be used in many application in field of artificial intelligence like in video cameras for security purpose and in robot this requires much things to do like image segmentation and the motion detection and to calculate distance of any object so stereo vision can be made in use for this methods thus this paper contains the algorithm for detecting motion and also smoothing filters to make output of two images smooth and to measure distance of any object i.e. blob detection the stereo ranging method is given i.e. novel algorithm. We will use novel algorithm for efficient motion detection and tracking of blob. It involves dividing video into image frames, converting frames into gray scale images, subtraction and thresholding of image frames, blob detection and combining blobs. As we all know that speed is also the important factor while making the motion detection the paralleling algorithm is explained for it. This paper also gives relationship of human vision with stereo vision and as we use to cameras in stereo vision there are problems like correspondence problem, camera calibration are explained and the feature and correlation based methods to solve this problems is given and the triangulation method is also made in use to compute depth.

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Stereo vision parallel algorithm correspondence camera calibration triangulation method blob detection