DocumentCode :
2307483
Title :
Human visual system inspired object detection and recognition
Author :
Mandal, Debashree ; Panetta, Karen ; Agaian, Sos
Author_Institution :
Dept. of Electr. & Comput. Eng., Tufts Univ., Medford, MA, USA
fYear :
2012
fDate :
23-24 April 2012
Firstpage :
145
Lastpage :
150
Abstract :
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.
Keywords :
feature extraction; object detection; object recognition; robot vision; computer vision techniques; feature extraction; generic framework; human visual sensitivity; human visual system inspired object detection; human visual system inspired object recognition; image morphology; robotic vision applications; Feature extraction; Humans; Image edge detection; Object detection; Training; Visual systems; Visualization; Feature Extraction; Human Visual System; Image Morphology; Object Detection; Robot Vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technologies for Practical Robot Applications (TePRA), 2012 IEEE International Conference on
Conference_Location :
Woburn, MA
Print_ISBN :
978-1-4673-0855-7
Type :
conf
DOI :
10.1109/TePRA.2012.6215669
Filename :
6215669
Link To Document :
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