Stereo matching algorithms are capable of generating depth maps from two images of the same scene taken simultaneously from two different viewpoints. Traditionally, a single cost function is used to calculate the disparity between corresponding pixels in the left and right images. In the present research, we have considered a combination of simple data costs. A new method to combine multiple data costs is presented and a fuzzy-based disparity selection method is proposed. Experiments with different combinations of parameters are conducted and compared through the Middlebury and Kitti Stereo Vision Benchmark.
SHETTY, AKHIL APPU; GEORGE, V.I; NAYAK, C GURUDAS; and SHETTY, RAVIRAJ
"Fuzzy logic-based disparity selection using multiple data costs for stereo correspondence,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 27:
1, Article 28.
Available at: https://journals.tubitak.gov.tr/elektrik/vol27/iss1/28