Automated Facial Feature Points Extraction

This paper proposes the extraction of geometric and texture feature of face automatically from front view. For extracting the geometric feature cumulative histogram approach is used and co-occurrence matrices are used to extract the texture feature of face. From the input image, face location is detected using the viola-Jones algorithm, from the structure of human face, 4 relevant regions such as left eye, right eye, nose and mouth regions are cropped named as object. For extracting the geometric feature histogram of each Object is computed and its cumulative histogram values are employed by varying different threshold values to create a new filtered binary image of each Object, then the corner end-point of each object (binary image) is detected using the linear search technique. For extracting the texture feature co-occurrence matrices of each object is determined, using this matrix, angular second moment, entropy, maximum probability of occurrence pixels, inverse difference, inverse difference moment , mean, contrast of each object is detected.