IEICE TRANSACTIONS on Information
Detecting Objectionable Images Using a New Skin Detection Method
Summary :
In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.9 pp.2288-2297
- Publication Date
- 2012/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.2288
- Type of Manuscript
- PAPER
- Category
- Pattern Recognition
Authors
Keyword
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Ali NADIAN GHOMSHEH, Alireza TALEBPOUR, "Detecting Objectionable Images Using a New Skin Detection Method" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 9, pp. 2288-2297, September 2012, doi: 10.1587/transinf.E95.D.2288.
Abstract: In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2288/_p
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@ARTICLE{e95-d_9_2288,
author={Ali NADIAN GHOMSHEH, Alireza TALEBPOUR, },
journal={IEICE TRANSACTIONS on Information},
title={Detecting Objectionable Images Using a New Skin Detection Method},
year={2012},
volume={E95-D},
number={9},
pages={2288-2297},
abstract={In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.},
keywords={},
doi={10.1587/transinf.E95.D.2288},
ISSN={1745-1361},
month={September},}
Copy
TY - JOUR
TI - Detecting Objectionable Images Using a New Skin Detection Method
T2 - IEICE TRANSACTIONS on Information
SP - 2288
EP - 2297
AU - Ali NADIAN GHOMSHEH
AU - Alireza TALEBPOUR
PY - 2012
DO - 10.1587/transinf.E95.D.2288
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2012
AB - In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.
ER -
English
