BIO-INSPIRED APPROACH FOR IMAGE VEHICLE DETECTION UNDER LOW ILLUMINATION

Zuojin Li, Wei Zhou, Liukui Chen, and Shangzhu Jin

Keywords

What pathway, vehicle detection, computing model, low illumination

Abstract

Camera-based vehicle detection under low illumination is a great challenge in intelligent transportation. Loud noise and insufficient colour information of the images hinder recognition quality of an interest target by traditional processing methods. To give full play to the strengths of bio-vision in graphic information processing and target recognition, this paper simulates the information processing and partition functions of its “what pathway, constructs a vision information processing model, and designs a computing method for image processing and recognition. Experiments under low illumination with 1,440 samples for vehicle detection have reached an average recognition rate of 92.1%, which proves this proposed method is able to improve the accuracy of vehicle detection by the intelligent transportation system.

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