An Efficient Edge Detection Algorithm for Facial Images in Image Mining

Image mining is a vital technique which is used to mine knowledge straightforwardly from image. It normally deals with the study and development of new technologies that allow easy analysis and interpretation of the images. It is an interdisciplinary endeavor that draws upon expertise in various fields like computer vision, image retrieval, matching and pattern recognition. Edge detection is very important terminology in image processing and for computer vision. Edge detection significantly reduces the amount of data and filters out ineffective information, while preserving the important structural properties in an image. It is in the forefront of image processing for object detection, it is vital to have a good understanding of edge detection algorithms. In the present study, comparative analyses of different edge detection operators in image processing are presented. It has been observed from this research the performance of Canny edge detection algorithm is much better then Mar-Hildreth algorithm for extracting edges from the facial images which are used for face detection. The performances of these edge detection algorithms are analyzed by applying performance factors and from the experimental results, it is observed that the Canny edge detection algorithm works better than Mar-Hildreth edge detection algorithms.