Adaptive pedestrian detection in infrared images using fuzzy enhancement and top-hat transform. (2017)

• Record Type: Journal Article
• Authors: Soundrapandiyan, Rajkumar; Mouli, P.V.S.S.R. Chandra
• Is Part Of: International journal of computational vision and robotics. Volume 7:Number 1/2(2017)
• Page Start: 49
• Page End: 67
• Publication Date: 2017
• Subjects: small target detection -- infrared images -- fuzzy set enhancement -- top-hat transform -- local adaptive thresholding -- pedestrian detection -- pedestrians -- fuzzy logic -- object detection -- fuzzy enhanced images; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

Infrared imaging is the order of the day. Infrared imaging finds its applications extensively in defence related areas. Pedestrian detection in IR image is a challenging problem. This paper addresses this problem using fuzzy-based enhancement followed by top-hat transform. The proposed method is adaptive in the sense that the parameters required for the process are calculated adaptively based on the image characteristics. Experimental results on the standard dataset show the robustness of the proposed method with 90% detection rate of pedestrians under different conditions and outperform the other existing methods.