Human visual system inspired object detection and recognition
Debashree Mandal, Karen A. Panetta, Sos С. Agaian · 2012
This paper presents a new generic framework for human visual system inspired object detection and recognition and introduces the idea of feature extraction based on the human visual sensitivity. These methods can greatly enhance robotic vision applications. Additionally a new computationally effective object detection algorithm is presented based on image morphology and visual sensitivity. This new method surpasses the performance of the existing method based on traditional edge detectors. We also present the effectiveness of the algorithm on under-illuminated images.