Article details

Title: Decision Fusion for Face Detection in Color Images
Author(s): Romana Oancea   Cristian Molder   Marius Cîrmaci         

Abstract: Face recognition in color images is important in various applications, such as smartcards, information security, law enforcement, entertainment, and so on. The recognition is divided into two main stages: (1) face detection in images, followed by (2) face recognition itself. Concerning the face detection step, the vast majority of studies use only one algorithm applied using a single color space, with limited performances. In this article, we propose the simultaneous use of several well-known color spaces (such as nRGB, YCbCr, HSV or YES) for constructing skin/non-skin models, followed by the use of decision fusion in every color space considered individually in order to enhance the detection performance. The results are presented considering a database of more than 600 color images of 480×720 pixels, with human subjects in various conditions and backgrounds.

Keywords: image processing, face detection, biometry.


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