Edge detection:Digital Image Processing
Abstract:
Edge detection is an important feature in computer supervision and image processing. In this paper, we discuss several digital image processing techniques in edge feature extraction. Firstly,we define keyterms,such as image,digitalimage,edge, Image noiseetc.leading to certain methods of image de-noising and edge detection. Edge detection includes operators such as Sobel, Prewitt and Roberts. Secondly, a comparative study is made to show that the Sobel operator gives best results.Finally, Edge extraction using edge histogram is taken into account. The edge extraction method proposed in this paper is feasible.
Index terms: digital image, edge detection, operators, edge histogram.
Introduction:
The edge is a set of those pixels whose grey have stepchange and rooftop change, and it exists between object andbackground, object and object, region and region, and betweenelement and element. Edge always indwells in twoneighboring areas having different grey level. It is the result ofgray level being discontinuous. Edge detection is a kind ofmethod of image segmentation based on range non-continuity.Image edge detection is one of the basal contents in the imageprocessing and analysis, and also is a kind of issues which areunable to be resolved completely so far. When image isacquired, the factors such as the projection, mix, aberranceand noise are produced. These factors bring on image feature’sblur and distortion, consequently it is very difficult to extractimage feature. Moreover, due to such factors it is also difficultto detect edge. The method of image edge and outlinecharacteristic 's detection and extraction has been research hotin the domain of image processing and analysis technique.
Edge feature extraction has been applied in many areaswidely. This paper mainly discusses about advantages anddisadvantages of several edge detection operators .In order to gainmore legible image outline, firstly the acquired image isfiltered and denoised. And then
Edge detection is an important feature in computer supervision and image processing. In this paper, we discuss several digital image processing techniques in edge feature extraction. Firstly,we define keyterms,such as image,digitalimage,edge, Image noiseetc.leading to certain methods of image de-noising and edge detection. Edge detection includes operators such as Sobel, Prewitt and Roberts. Secondly, a comparative study is made to show that the Sobel operator gives best results.Finally, Edge extraction using edge histogram is taken into account. The edge extraction method proposed in this paper is feasible.
Index terms: digital image, edge detection, operators, edge histogram.
Introduction:
The edge is a set of those pixels whose grey have stepchange and rooftop change, and it exists between object andbackground, object and object, region and region, and betweenelement and element. Edge always indwells in twoneighboring areas having different grey level. It is the result ofgray level being discontinuous. Edge detection is a kind ofmethod of image segmentation based on range non-continuity.Image edge detection is one of the basal contents in the imageprocessing and analysis, and also is a kind of issues which areunable to be resolved completely so far. When image isacquired, the factors such as the projection, mix, aberranceand noise are produced. These factors bring on image feature’sblur and distortion, consequently it is very difficult to extractimage feature. Moreover, due to such factors it is also difficultto detect edge. The method of image edge and outlinecharacteristic 's detection and extraction has been research hotin the domain of image processing and analysis technique.
Edge feature extraction has been applied in many areaswidely. This paper mainly discusses about advantages anddisadvantages of several edge detection operators .In order to gainmore legible image outline, firstly the acquired image isfiltered and denoised. And then
References: [1] “Digital Image Processing by R.C. Gonzalez and R.E.Woods. [2]http://en.wikipedia.org/wiki/Noise_reduction [3]Edge Feature Extraction Based on Digital Image Processing Techniques: Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China September 2008. [4]Efficient Use of Local Edge Histogram Descriptor by Dong Kwon Park,YoonSeokJeon,Chee Sun Won.