Abstract
Image Processing is a method to perform working or an action on an image to intensify and upgrade it or to bring out some useful information. It is a type of signal processing in which input is an image and output may be image or features relating with that image. Nowadays, image processing is becoming a promptly growing technology. Image Processing is also used as a technology in core research area. It’s upper hand is able to be seen in the application such as face detection, speech recognition, speech processing, video compression and audio compression etc,. This paper encourages the comparison between edge detection technique which is a advanced computer technology being used in a variety of applications that identifies human faces in digital images. Edge Detection includes a variety of mathematical methods that aims at identifying points in a digital image at which the image brightness sharply changes or have discontinuities. The point at which image brightness changes sharply are typically organized into a set of curved line segments called edges[4]. Edge Detection is the fundamental tool in image processing, machine vision and computer vision. In this paper, the comparison of two edge detection algorithms will be done namely, Canny edge detection and Sobel edge detection to extract edges from facial images.
Keywords: Edge detection, Object detection and recognition, Image Segmentation, Canny Operator, Sobel Operator.