Computing disparity map using minimum sum belief propagation for stereo pair images

Stereo matching between two images is done by computing disparity of all points on the object. The process involves identifying corresponding points in stereo image and finding the horizontal shift. Presently, there is no method that finds the shift in the corresponding points between left and right images; this is due to non-availability of procedure to identify the group of pixel in the right and left image of the same object. The available local methods either use window or feature to find shift in a stereo image. In these methods, 'finalising size of the window' or 'deciding the correct feature' remains an unresolved issue. On the other hand, global methods use graph theory and probability theory to find the shift efficiently. The belief propagation algorithm is one of the global method devised to offer computationally efficient approach with good results. This paper has applied 'minimum sum belief propagation' method for message updates with linear 'quadratic function' for computation of horizontal shift in stereo image. The results with the computational estimations are presented hereby and based on these results, suggestive comments on effectiveness of update which indicate strategy versus type of the image are also mentioned.