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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Mohammed Razzok
Hassan II University
Computer Science & IT Engineering

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A new pedestrian recognition system based on edge detection and different census transform features under weather conditions Mohammed Razzok; Abdelmajid Badri; Ilham El Mourabit; Yassine Ruichek; Aïcha Sahel
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp582-592

Abstract

Pedestrian detection has so far achieved great success in normal illumination, while pedestrians captured in extreme weather are often ignored. This paper investigates the importance of studying the effects of weather conditions on the recognition task, such as blurring and low contrast. Many image restoration techniques have recently been proposed, but are still insufficient to remove weather effects from images. We present our strong new pedestrian recognition system against climate situations, which is based on locating contours cues by applying multiple edge filters and extracting multiple features from images such as census transform (CT), modified census transform (MCT), and local gradient pattern (LGP) without performing any image restoration algorithm. The next stage involves finding the most discriminative characteristics using feature selection (FS) techniques. Finally, we use the final feature vector as an input to a radial basis function-based support vector machine classifier (RbfSVM) for pedestrian recognition. Experiments are performed on the daimler pedestrian classification benchmark dataset. Results show that the area under the curve (AUC) and the detection rate of our model are less affected by weather conditions compared to other common models like histogram of oriented gradients (HOG) and gabor filter bank (GFB) detectors.
Co-Authors Abdelmajid Badri Aicha Sahel Ilham El Mourabit Yassine Ruichek