edgefeatureextractionbasedondigitalimageprocessingtechniques-外文文獻(xiàn)-資料下載頁(yè)
2025-05-12 18:54本頁(yè)面
【導(dǎo)讀】³feasible.background,objectandobject,regionandregion,andbetween
【正文】 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。 the other is direction of gradient. According to edge pixels gradient’s similarity on these two aspects, the edge pixels can be connected. Specific speaking, if the pixel(s,t) is in the neighbor region of the pixel(x,y)and their gradient magnitudes and gradient directions must satisfy two conditions (16) and (17) respectively, then the pixels in(s,t) and the pixels in(x,y) can be connected. The closed boundary will be obtained if all edge pixels are judged and connected. fxy fst T??≤K244。K248。K245。K249。K244。K248。K245。 (16) xy xt A??≤K244。K248。K245。K249。K244。K248。K245。 (17) Where T is magnitude threshold, A is angle threshold. V. C ONCLUSION These edge detection operators can have better edge effect under the circumstances of obvious edge and low noise. But the actual collected image has lots of noises. So many noises may be considered as edge to be detected. In order to solve the problem, wavelet transformation is used to denoise in the paper. Yet its effect will be better if those simulation images processed above are again processed through edge thinning and tracking. Although there are various edge detection methods in the domain of image edge detection, certain disadvantages always exist. For example, restraining noise and keeping detail can’t achieve optimal effect simultaneously. Hence we will acquire satisfactory result if choosing suitable edge detection operator according to specific situation in practice. REFERENCES[1] Lei Lizhen, Discussion of digital image edge detection method, Mapping aviso, 2020, 3:4042. [2] Lai Zhiguo, etc, “Image processing and analysis based on MATLAB” , Beijing: Defense Industry Publication, 2020,4. [3] Chen Wufan, “Wavelet analysis and its application in image manipulation” ,Beijing: Science Publishing House, 2020. [4] Kenh RC, “Digital image processing[M]” , Beijing: Electronics Industry Publication, 1998. [5] Wang Xiaodan etc, Image analysis and design based on MATLABimagery processing [M], Xi’an: Publishing House of Xi’an University of Electrical Science and Technology, 2020, 9. [6] Ma Yan, and Zhang Zhihui, Several edge detection operators paration, Industry and mining automation, 2020, (1): 5456. [7] Gao Cheng, and Lai Zhiguo etc, Image analysis and application based on MATLAB, Beijing: Publishing House of National defence industry, 2020, 4: 133175. [8] Wang Zhengyao, Edge detection of digital image[Master paper], Xi’an: Xi’an Jiaotong University, 2020. [9] HeungSoo Kim and JongHwan Kim. A twostep detection algorithm from the intersecting chords. Pattern Recognition Letters. 2020, 22:787798. [10] Canny J F. A putatioal approach tO edge detection[J]. IEEE Trans on PAMI, 1985, 8(6): 679698. [11] Marr D. Theory of edge detection[J]. Proc Roy Soc, 1980, B(27): 187217. 2324
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