چکیده (انگلیسی):

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 Cr of YCbCr 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 YCbCr
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.