Radiometric Invariant Dense Disparity Estimation for Real Time Stereo Correspondence

Computer stereo vision tries to mimic human vision by grabbing multiple views of the same scene and cognizing it. The stereo correspondence will find out the matching pixels between the two views based on the Lambertian criteria, which results in disparity. The distance of the objects from the camera can be calculated using this disparity. But in the real world scenario, this Lambertian assumption may not work always due to the radiometric variation between the image pairs and the conventional approaches results in erroneous disparity. In this work, for doing the radiometric invariant stereo matching, the simple local binary pattern is used. The correspondence is done by using semi global block matching method, which can handle the depth changes of curved surfaces and slanting surfaces by adding suitable penalty terms. The performance evaluation of the proposed shows lesser error rate in the range of 0.14% - 0.3883% and run time requirement of 0.20 milliseconds only. This radiometric invariant stereo correspondence attains accuracy as that of global method with run time speed as that of local method and is suitable for most of the real time stereo vision applications.