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Open Access Algorithm for Face Extraction Based on Lip Detection

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This paper proposes a new and simple algorithm for face extraction from a color image. The approach detects the lip region in a face object. First, the lip- and skin-color pixels in an image are extracted on the basis of statistical probability analysis. These lip- and skin-color pixels are segmented separately by using binary image processing techniques to produce lip- and skin-color regions. Each region that has a skin-color region and one or more lip-color regions as its subset regions is nominated as a face candidate. To detect only the face objects from the face candidates, the algorithm evaluates the values of seven pattern variables of those face candidates. A face candidate with all its seven pattern variable values within the valid range values of face object class is detected as a face object. Verifications of the proposed algorithm were provided by the experimental results that gave 91.8% detection of face objects from 104 sample images. This is significant for locating or detecting the faces in color images.
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Document Type: Research Article

Publication date: January 1, 1997

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  • The Journal of Imaging Science and Technology (JIST) is dedicated to the advancement of imaging science knowledge, the practical applications of such knowledge, and how imaging science relates to other fields of study. The pages of this journal are open to reports of new theoretical or experimental results, and to comprehensive reviews. Only original manuscripts that have not been previously published, nor currently submitted for publication elsewhere, should be submitted.

    IS&T's JIST-first publication option allows authors wishing to present their work at conferences, but have a journal citation for their paper, to submit a paper to JIST that follows the same rigorous peer-review vetting and publication process as traditional JIST articles, but with the benefit of a condensed time-to-publication time frame and guaranteed conference presentation slot.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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