Face detection using sketch operators and vertical symmetry

  • Authors:

  • Hyun Joo So;Mi Hye Kim;Yun Su Chung;Nam Chul Kim

  • Affiliations:

  • Laboratory for Visual Communications, School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu, Korea;Laboratory for Visual Communications, School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu, Korea;Biometric Chipset Technology Research Team, Electronics and Telecommunications, Research Institute, Daejeon, Korea;Laboratory for Visual Communications, School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu, Korea

  • Venue:
  • FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
  • Year:
  • 2006

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Abstract

In this paper, we propose an algorithm for detecting a face in a target image using sketch operators and vertical facial symmetry (VFS). The former are operators which effectively reflect perceptual characteristics of human visual system to compute sketchiness of pixels and the latter means the bilateral symmetry which a face shows about its central longitudinal axis. In the proposed algorithm, horizontal and vertical sketch images are first obtained from a target image by using a directional BDIP (block difference inverse probabilities) operator which is modified from the BDIP operator. The pair of sketch images is next transformed into a generalized symmetry magnitude (GSM) image by the generalized symmetry transform (GST). From the GSM image, face candidates are then extracted which are quadrangular regions enclosing the triangles that satisfy eyes-mouth triangle (EMT) conditions and VFS. The sketch image for each candidate is obtained by the BDIP operator and classified into a face or nonface by the Bayesian classifier. Among the face candidates classified into faces, one with the largest VFS becomes the output where the EMT gives the location of two eyes and a mouth of a target face. If the procedure detects no face, then it is executed again after illumination compensation on the target image. Experimental results for 1,000 320x240 target images of various backgrounds and circumstances show that the proposed method yields about 97% detection rate and takes a time less than 0.25 second per target image.