Using self-organizing fuzzy network with support vector learning for face detection in color images

Juang, Chia‐Feng; Shiu, Shen-Jie

doi:10.1016/j.neucom.2007.11.007

Cited by 31 publications

(11 citation statements)

References 23 publications

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“…[32] proposed an algorithm based on facial saliency map. Juang and Shiu [25] used self-organizing Takagi-Sugeno-type fuzzy network with support vector machine, which is applied to skin color segmentation. Gasparini and Schettini [16] used Genetic Algorithm to find the classification boundaries between skin and non-skin pixels based on multiple color spaces.…”

Section: Other Methodsmentioning

confidence: 99%

Skin color modeling for face detection and segmentation: a review and a new approach

Chen

Wang

Jiang

et al. 2014

Multimed Tools Appl

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Detecting skin-colored pixels, although seems a straightforward easy task, has proven to be quite a challenging task in images that are captured under complex unconstrained imaging conditions. Color segmentation is an important method of segmenting the body in images. In this paper, we first provides a review of skin color modeling research works for face detection. In particular, we focus on discussing the challenges of skin color modeling, detection, and segmentation, and then we present the skin color modeling and region-based skin segmentation. We also propose a new approach to analyze the hue characteristics of monitoring personnel in coal mine. We determine the skin color boundaries of the miners using the boundary detection method based on the response of visual hue. And then, we apply to determining hue area method using dual hue detector to segment skin color for miners. Experiments show that the method has excellent ability to segment skin regions of miners. We also summarize the most widely used methods for skin detection approaches and collecting their numerical evaluation results.

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Section: Other Methodsmentioning

confidence: 99%

Skin color modeling for face detection and segmentation: a review and a new approach

Chen

Wang

Jiang

et al. 2014

Multimed Tools Appl

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“…That is, if input regions near the scaled values of H=0 and H=1 are non-skin regions [4].Juang and Chang used scheme of HSV color space Like the previous system , They believed To produce a good segmentation result, must be a suitable threshold is selected. Using a fixed threshold for all public images segmentation result does not provide satisfactory.…”

Section: Skin Color Segmentation Algorithmsmentioning

confidence: 99%

Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)

Iraji¹,

Tosinia²

2012

IJIGSP

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Abstract-In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis) methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis) has less error and system worked more accurate and appropriative than prior methods.

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“…Juang et al [24,25,26] proposed a selforganizing Takagi-Sugeno-type fuzzy network with support vector learning (SOTSFN-SV). They successfully applied it to several real-world datasets.…”

Section: Hybrid Approaches Using Clusteringmentioning

confidence: 99%

On the usefulness of fuzzy SVMs and the extraction of fuzzy rules from SVMs

Moewes¹,

Kruse²

2011

Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)

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In this paper we reason about the usefulness of two recent trends in fuzzy methods in machine learning. That is, we discuss both fuzzy support vector machines (FSVMs) and the extraction of fuzzy rules from SVMs. First, we show that an FSVM is identical to a special type of SVM. Second, we categorize and analyze existing approaches to obtain fuzzy rules from SVMs. Finally, we question both trends and conclude with more promising alternatives.

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Using self-organizing fuzzy network with support vector learning for face detection in color images

Cited by 31 publications

References 23 publications

Skin color modeling for face detection and segmentation: a review and a new approach

Skin color modeling for face detection and segmentation: a review and a new approach

Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)

On the usefulness of fuzzy SVMs and the extraction of fuzzy rules from SVMs

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