Stereo matching algorithm for autonomous vehicle navigation using integrated matching cost and non-local aggregation

Madiha Zahari, Rostam Affendi Hamzah, Nurulfajar Abd Manap, Adi Irwan Herman


Stereo matching algorithm plays an important role in an autonomous vehicle navigation system to ensure accurate three-dimensional (3D) information is provided. The disparity map produced by the stereo matching algorithm directly impacts the quality of the 3D information provided to the navigation system. However, the accuracy of the matching algorithm is a challenging part to be solved since it is directly affected by the surrounding environment such as different brightness, less texture surface, and different image pair exposure. In this paper, a new framework of stereo matching algorithm that used the integration of census transform (CT) and sum of absolute difference (SAD) at the matching cost computation step, non-local cost aggregation at the second step, winner take all strategy at the third step, and a median filter at the final step to minimize disparity map error. The results show that the accuracy of the disparity map is improved using the proposed methods after some parameter adjustment. Based on the standard Middlebury and KITTI benchmarking dataset, it shows that the proposed framework produced accurate results compared with other established methods.


Autonomous; Disparity; Matching cost; Stereo matching

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).