Skin detection in images or videos plays a vital role in a wide range of image processing applica... more Skin detection in images or videos plays a vital role in a wide range of image processing applications like face detection, face tracking, gesture analysis, human-computer interaction etc. Due to its high processing speed and invariant against rotation, it has received significant interest in pattern recognition and computer vision. The robustness of skin detection using color information depends on real world conditions such as background, noise, change of intensity and lightening effects. This situation can be improved by using texture as a descriptor to extract skin pixels in images. This study proposes color based skin detection algorithm (fusion of Cheddad's approach with C r of YC b C r color space) with a texture based skin location algorithm called Modified Weber's Law Descriptions (MWLD) to evaluate region features. MWLD is based on the fact that the Human Visual System (HVS) is more sensitive in lumens contrast than absolute luminance values. In MWLD, the differential excitation and gradient orientation of the current pixel are considered to extract the texture features. For differential excitation, Just Noticeable Distortion (JND) is also used. Due to the absence of red component in Cheddad's new color space for skin detection, the detection rate is not good for real time applications. To improve this situation, the Cr component of YC b C r color space is included to obtain the color features. According to experimental results, the proposed method exhibits satisfactory performance in terms of True Positive Rate (TPR), False Positive Rate (FPR) and Accuracy with wide variations in size, color and orientation. Different window sizes for differential excitation such as 3×3, 5×5 and 7×7 are also taken to check the performance.
International Journal of Computer Applications, 2012
Skin is the most widely used primitive in human image processing research and computer vision wit... more Skin is the most widely used primitive in human image processing research and computer vision with application ranging from face detection and person tracking to pornography filtering. It has proven to be a useful and robust cue for detecting human parts in images since (i) it is invariant to orientation and size (ii) it gives extra dimension compared to gray scale methods and (iii) it is fast to process. The main problems with the robustness of skin color detection depend on illumination condition, it varies between individuals, many everyday life objects are skin color like and skin color is not unique. To detect skin tone in images with this complex background, we presented a method based on hybrid approach. In this approach, the Cheddad’s approach is combined with Cr of YCbCr color space. In Cheddad’s approach, the red channel is discarded. Only green and blue channels are used to find the skin tones. Due to the absence of red channel, this approach is not working properly in im...
Skin is arguably the most widely used primitive in human image processing research and computer v... more Skin is arguably the most widely used primitive in human image processing research and computer vision with application ranging from face detection and person tracking to pornography filtering. It has proven to be useful and robust cue for detecting human parts in images since (i) it is invariant to orientation and size (ii) it gives extra dimension compared to gray scale methods and (iii) it is fast to process. The main problems with the robustness of skin color detection are however depends on illumination condition, it varies between individuals, many everyday life objects are skin color like and skin color is not unique. Environments comprehensive survey in this topic is missing. The work presented in this paper is a survey of the most frequently used methods and techniques and their numerical evaluation results. General Terms Image Processing, Face Detection.
Skin detection in images or videos plays a vital role in a wide range of image processing applica... more Skin detection in images or videos plays a vital role in a wide range of image processing applications like face detection, face tracking, gesture analysis, human-computer interaction etc. Due to its high processing speed and invariant against rotation, it has received significant interest in pattern recognition and computer vision. The robustness of skin detection using color information depends on real world conditions such as background, noise, change of intensity and lightening effects. This situation can be improved by using texture as a descriptor to extract skin pixels in images. This study proposes color based skin detection algorithm (fusion of Cheddad's approach with C r of YC b C r color space) with a texture based skin location algorithm called Modified Weber's Law Descriptions (MWLD) to evaluate region features. MWLD is based on the fact that the Human Visual System (HVS) is more sensitive in lumens contrast than absolute luminance values. In MWLD, the differential excitation and gradient orientation of the current pixel are considered to extract the texture features. For differential excitation, Just Noticeable Distortion (JND) is also used. Due to the absence of red component in Cheddad's new color space for skin detection, the detection rate is not good for real time applications. To improve this situation, the Cr component of YC b C r color space is included to obtain the color features. According to experimental results, the proposed method exhibits satisfactory performance in terms of True Positive Rate (TPR), False Positive Rate (FPR) and Accuracy with wide variations in size, color and orientation. Different window sizes for differential excitation such as 3×3, 5×5 and 7×7 are also taken to check the performance.
International Journal of Computer Applications, 2012
Skin is the most widely used primitive in human image processing research and computer vision wit... more Skin is the most widely used primitive in human image processing research and computer vision with application ranging from face detection and person tracking to pornography filtering. It has proven to be a useful and robust cue for detecting human parts in images since (i) it is invariant to orientation and size (ii) it gives extra dimension compared to gray scale methods and (iii) it is fast to process. The main problems with the robustness of skin color detection depend on illumination condition, it varies between individuals, many everyday life objects are skin color like and skin color is not unique. To detect skin tone in images with this complex background, we presented a method based on hybrid approach. In this approach, the Cheddad’s approach is combined with Cr of YCbCr color space. In Cheddad’s approach, the red channel is discarded. Only green and blue channels are used to find the skin tones. Due to the absence of red channel, this approach is not working properly in im...
Skin is arguably the most widely used primitive in human image processing research and computer v... more Skin is arguably the most widely used primitive in human image processing research and computer vision with application ranging from face detection and person tracking to pornography filtering. It has proven to be useful and robust cue for detecting human parts in images since (i) it is invariant to orientation and size (ii) it gives extra dimension compared to gray scale methods and (iii) it is fast to process. The main problems with the robustness of skin color detection are however depends on illumination condition, it varies between individuals, many everyday life objects are skin color like and skin color is not unique. Environments comprehensive survey in this topic is missing. The work presented in this paper is a survey of the most frequently used methods and techniques and their numerical evaluation results. General Terms Image Processing, Face Detection.
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