The main target of stereo matching algorithms is to find out the three dimensional (3D) distance, or depth of objects from a stereo pair of images. Depth information can be derived from images using disparity map of the same scene. There are many applications of computer vision like People tracking, Gesture recognition, Industrial automation and inspection, Security and Biometrics, Three-dimensional modeling, Web and Cloud, Aerial surveys etc. There are large categories of stereo algorithms which are used for finding the disparity or depth. This paper presents a proposed stereo matching algorithm to obtain depth map, enhance and measure. The hybrid mathematical process of the algorithm are color conversion, block matching, guided filtering, Minimum disparity assignment design, mathematical perimeter, zero depth assignment, combination of hole filling and permutation of morphological operator and last non linear spatial filtering. Our algorithm is produce noise less, reliable, smooth and efficient depth map. We obtained the results with ground truth image using Structural Similarity Index Map (SSIM) and Peak Signal to Noise Ratio (PSNR).
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