A stereo matching algorithm for coal mine underground images based on threshold and weight under Census transform

• Published in: Méitàn kēxué jìshù Vol. 52; no. 6; pp. 216 - 225
• Main Authors: Chunyu YANG, Ziru SONG, Xin ZHANG
• Format: Journal Article
• Language: Chinese
• Published: Editorial Department of Coal Science and Technology 01.06.2024
• Subjects: binocular vision; census transform; driverless auxiliary transport vehicle; salt-and-pepper noise; stereo matching
• ISSN: 0253-2336
• DOI: 10.12438/cst.2023-1169

Binocular image stereo matching is a key technology to realize autonomous obstacle avoidance and visual reconnaissance of unmanned auxiliary transport vehicles in coal mines. However, factors such as high dust and unstable lighting conditions in coal mines can lead to Salt-and-pepper noise in the images collected by the visual sensor, resulting in a high stereo matching error rate. Therefore, a Census stereo matching algorithm based on the combination of threshold and weight is proposed to reduce the impact of Salt-and-pepper noise on stereo matching. The main contributions include: ① threshold processing is carried out on the gray values of all pixels in the support window to remove the pixels with maximum and minimum gray values in the support window and solve the impact of outlier on the weighted fusion; ② the four diagonal pixels corresponding to the center point are weighted and fused to replace the center point pixel. Select pixel points along the four diagonal lines intersecting at the center pixel, wi