Face Detection with Modified Ellipse Hough Transform and Eye-Brow Block Searching
Date Issued
2004
Date
2004
Author(s)
Wang, Wei-Jun
DOI
zh-TW
Abstract
This study proposes a modified ellipse Hough transform(MEHT) as well as robust noise filtering and eye-brow block searching(RNFEBS) for face detection based on ellipticity, contrast and geometrical features of objects in an image. As for the face detection in a static gray level image with complex background, the most valuable information is the elliptical shapes of faces and the geometrical features of eyes. With MEHT, the position of the face center is easily estimated. And then, RNFEBS is applied afterwards to search for eye-brow block and locate eyes pair. The location and size of face could be decided accordingly.
Different from the accumulator design of traditional Hough transform, the MEHT developing two types of accumulator which are related to both ellipticity and contrast of objects in an image. The factor KM and KA in the accumulators could be turned to suppress the influence of contrast on the accumulator and achieve the lower contribution than ellipticity. MEHT is very robust for the detection of nonstandard ellipse with complex background in an image if the factor KM and KA is carefully chosen based on noise margin. The positions of eye-brow block, eyes pair and face could be obtained accordingly based on eyes’ geometrical features by RNFEBS. This approach developed in the study is proved to be high efficient and accurate.
Subjects
橢圓偵測
人臉偵測
霍氏轉換
人眼偵測
ellipse detection
Hough transform
face detection
eyes detection
Type
thesis
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