مشاهده مشخصات مقاله
Skin Detection using Contourlet Texture Analysis
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نویسنده (ها) |
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Mehran Fotouhi
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Mohammad H. Rohban
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Shohreh Kasaei
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
A combined texture- and color-based skin detection
is proposed in this paper. Nonsubsampled contourlet
transform is used to represent texture of the whole
image. Local neighbor contourlet coefficients of a pixel
are used as feature vectors to classify each pixel.
Dimensionality reduction is addressed through
principal component analysis (PCA) to remedy the
curse of dimensionality in the training phase. Before
texture classification, the pixel is tested to determine
whether it is skin-colored. Therefore, the classifier is
learned to discriminate skin and non-skin texture for
skin colored regions. A multi-layer perceptron is then
trained using the feature vectors in the PCA reduced
space. The Markov property of images is addressed in
post-processing to join separate neighbor skin detected
regions. Comparison of the proposed method with
other state-of-the-art methods shows a lower false
positive rate with a little decrease in true positive rate. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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خرید مقاله
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