edgefeatureextractionbasedondigitalimageprocessingtechniques-外文文獻(參考版)
2025-05-17 18:54本頁面
【正文】 K245。K244。K245。 (16) xy xt A??≤K244。K248。K249。K248。canny operator can produce two information including the border gradient direction and intensity. Canny operator is actually using templates of different directions to do convolution to the image respectively. Then the mostly direction is taken. From the viewpoint of positioning accuracy, canny operator is better than the other operators. Therefore, this method is not easily disturbed by noise and can keep the good balance between noise and edge detection. It can detect the true weak edge. D. Binary morphology Mathematical morphology is a new method applied in image processing. The basic idea is to measure and extract the corresponding shape from image with structural elements having stated form. So that the image processing and analyzing can be pleted [2]. Using mathematical morphology to detect the edge is better than using differential treatment. Because it is not sensitive to noise, and the edge extracted is relatively smooth. Binary image is also known as blackandwhite image. The object can be easily identified from the image background. So we adopt the bination of binary image and mathematical morphology to detect edge. It is called Binary morphology. Suppose that the region is shown in form of the set A. Its border is ( )Aβ . B is an appropriate structure element, and it is symmetrical around the origin. Firstly we corrupt A with B recorded as { | ( ) }xA BxB AΘ= ? , where ( )xB is a translation B along the vector. The interior of region is available with A BΘ . And ( )A AB?Θis the borderline naturally. Then ()Aβ is obtained. The equation of edge extraction can be said () ( )A AABβ =?Θ.Structuring element is larger, the edge gained will be wider. E. Simulative results analysis In order to know about the advantages and disadvantages of these edge detection operators, we detect edge using these different operators respectively. The simulation results are shown in Fig. 9 and Fig. 10. original image Binary image edge extractionFig. 9 detecting edge with Binary morphology original image roberts operator sobel operator prewitt operator canny operator log operator Fig. 10 several edge detection algorithm parison From the simulation results we can conclude that: the effect of detecting edge with sobel operator after wavelet denoising and with Binary morphology directly is better. So these two methods can be used. But finally we choose Binary morphology method based on specific measurement errors. IV. BORDERLINE CLOSED Although image is denoised before detecting edge, yet noises are still introduced when detecting edge. When noise exists, the borderline, which is obtained using derivative algorithm to detect image, usually produces the phenomenon of break. Under this situation, we need to connect the edge pixels. Thus, we will introduce a kind of method closing the borderline with the magnitude and direction of pixels gradient. The basis of connecting edge pixels is that they have definite similarity. Two aspects’ information can be gained 2323using gradient algorithm to process image. One is the magnitude of gradient。 x,yK245。s detection and extraction has been research hot in the domain of image processing and analysis technique. Edge feature extraction has been applied in many areas widely. This paper mainly discusses about advantages and disadvantages of several edge detection operators applied in the cable insulation parameter measurement. In order to gain more legible image outline, firstly the acquired image is filtered and denoised. In the process of denoising, wavelet transformation is used. And then different operators are applied to detect edge including Differential operator, Log operator, Canny operato
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