title: Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body.
abstract: With higher demand from users, surveillance systems are currently being designed to provide more information about the observed scene, such as the appearance of objects, types of objects, and other information extracted from detected objects. Although the recognition of gender of an observed human can be easily performed using human perception, it remains a difficult task when using computer vision system images. In this paper, we propose a new human gender recognition method that can be applied to surveillance systems based on quality assessment of human areas in visible light and thermal camera images. Our research is novel in the following two ways: First, we utilize the combination of visible light and thermal images of the human body for a recognition task based on quality assessment. We propose a quality measurement method to assess the quality of image regions so as to remove the effects of background regions in the recognition system. Second, by combining the features extracted using the histogram of oriented gradient (HOG) method and the measured qualities of image regions, we form a new image features, called the weighted HOG (wHOG), which is used for efficient gender recognition. Experimental results show that our method produces more accurate estimation results than the state-of-the-art recognition method that uses human body images.
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. nguyentiendat@dongguk.edu.
authors.forename: Dat Tien
authors.initials: DT
authors.lastname: Nguyen
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. parkgr@dongguk.edu.
authors.forename: Kang Ryoung
authors.initials: KR
authors.lastname: Park
mesh_terms: D000465:Algorithms; D015374:Biosensing Techniques / Q000379:methods*; D018594:Human Body; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D008027:Light; D010363:Pattern Recognition, Automated
keywords: gender recognition; image quality assessment; thermal camera image; visible light camera image