Face Detection Technology Based on Skin Color Segmentation and Template Matching

Chen, Aiping; Pan, Lian; Tong, Yaobin; Ning, Ning

doi:10.1109/etcs.2010.465

Cited by 21 publications

(11 citation statements)

References 1 publication

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“…We use 90% of the gathered skin and non-skin pixels for training and 10% for testing performance of the network. Table 1 has shown the detection rates for the proposed fuzzy rule based and NNbased skin detection method along by the results of Aiping et al [3] skin detection algorithm. Experimental results show that the fuzzy rule based system represent better performance in comparison with Aiping et al [3] and NNbased approaches.…”

Section: Resultsmentioning

confidence: 99%

“…Table 1 has shown the detection rates for the proposed fuzzy rule based and NNbased skin detection method along by the results of Aiping et al [3] skin detection algorithm. Experimental results show that the fuzzy rule based system represent better performance in comparison with Aiping et al [3] and NNbased approaches. Figure 4 demonstrate the result of applying the proposed method on some images with complex background step by step.…”

Section: Resultsmentioning

confidence: 99%

“…In the first group, skin classifier is defined based on explicit definition of the skin cluster boundary of skin color distribution in a specified color space. Aiping et al [3] define an oval shape cluster for skin color distribution in YCbCr color space. The key idea of the non-parametric skin modeling methods is to estimate skin color distribution from the training data without deriving an explicit model of the skin color.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Skin detection using fuzzy rule base system

Shemshaki¹,

Amjadifard²

2011

The 5th International Conference on Automation, Robotics and Applications

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Skin detection is the process of finding skin pixels in a given color image. In this paper, we propose a novel fuzzy rule based system for robust and fast skin detection in color images. The proposed fuzzy system models the skin color distribution in HSV color space. Using the fuzzy model, skin likelihood of the pixel is calculated and if it exceeds a threshold then this pixels is considered as skin pixel. Also we proposed a multi layer perceptron neural network for skin classifier and compare its performance with the proposed fuzzy rule based method.Experimental results show effectiveness of the proposed fuzzy rule based method in comparison with the neural network based and other previous approaches.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Skin detection using fuzzy rule base system

Shemshaki¹,

Amjadifard²

2011

The 5th International Conference on Automation, Robotics and Applications

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“…Facial image segmentation plays an essential role in some face detection systems in helping to extract only face part of a given large image based on skin-colors and non skin-colors classification [13].…”

Section: Facial Image Segmentationmentioning

confidence: 99%

Efficient Method of Visual Feature Extraction for Facial Image Detection and Retrieval

Alattab

Kareem

2012

2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation

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Due to the significant increase in the already huge collection of digital images that we have today, it has become imperative to find efficient methods for the archival and retrieval of these images. In this research, a content basedhuman facial image detection and retrieval model is proposed for retrieving facial images of humans based on their visual content from an image database. The research proposes a technique of face segmentation based on which a new method of features extraction from the human face is devised. The capability and effectiveness of the color space models (RGB, HSV, and HSI) on facial image retrieval technique are also investigated. Eigenfaces features are used as a domain specific visual content to extract the characteristic feature images of the human facial images, while the color histogram of the facial image is used as a general visual content. Viola-Jones face detection method is employed to obtain the location, extent and dimensions of each face. Moreover, for the measurement of distance and classification purposes, Euclidean distance is utilized. The sample image database consists of 1500 local facial images of one hundred and fifty participants from the University of Malaya (UM), Kuala Lumpur, and some of their friends and families outside the UM. Several experiments based on precision and recall approach were conducted to evaluate the proposed methods. The retrieval result of the facial image given by the proposed method showed excellent improvement comparing to those achieved when using the traditional method of visual features extraction.

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“…Skin color is the most discriminative feature in case of making difference between faces and background region. The studies show that difference between peoples' skin color is caused by difference in brightness and different people's skin color distributions can be clustered in the color space without brightness [6]. It is feasible to extract face regions from a given image using skin color segmentation.…”

Section: A Skin Color Segmentationmentioning

confidence: 99%

Lip Segmentation Using Geometrical Model of Color Distribution

Shemshaki¹,

Amjadifard²

2011

2011 7th Iranian Conference on Machine Vision and Image Processing

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An accurate and robust lip region detection algorithm based on skin and lip color segmentation is presented in this paper. Here skin and lip color analysis performs in chromatic and YCbCr color space respectively. The proposed algorithm defines geometrical models for skin and lip color distribution in order to detect skin and lip pixels in color image. The proposed algorithm performs lip detection in two stages. First skin pixels are detected in a given color image and face candidates are extracted. Then lip pixels are investigated within face candidates. We propose a segmentation method based on horizontal and vertical accumulation of the image pixel values. Experimental results show that the proposed method detects lips effectively with high accuracy.

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Face Detection Technology Based on Skin Color Segmentation and Template Matching

Cited by 21 publications

References 1 publication

Skin detection using fuzzy rule base system

Skin detection using fuzzy rule base system

Efficient Method of Visual Feature Extraction for Facial Image Detection and Retrieval

Lip Segmentation Using Geometrical Model of Color Distribution

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