基于数学形态学的边缘检测的改进算法-本科生毕业设计外文翻译

基于数学形态学的边缘检测的改进算法-本科生毕业设计外文翻译内容摘要：

each pixel if the directions have the biggest difference (such as the horizontal direction) explain that the edge will incline to the vertical the structural elements which have the same directions with the template of difference (the structure element in the horizontal). 41/m m mi i iinn   . Fusion Processing: Structure element is the basic element of mathematics morphology。 the structural elements may also affect edge detection results with different scales and example, Literature [13] uses single scale structure element,the edge of detection is not so plete. After the analysis and parison,this paper adopts the Omanidirectional muftiscale structural elements for edge to the improved operation (15),this paper puts forward a new algorithm for edge detection: 21451()mmmmm i miEEE x G i Among them,is the image edge that is obtained by using structural elements with different ,we put the structural elements of 3x3size of different orientations 1 1 1 11 2 3 4( : : : )b b b b into formula(15) respectively, fuse together the detection results to get the image edge 1E .Then, we use the structural elements of 5 x5size of xx 科技学院 2020 届本科生毕业设计（论文）外文翻译 6 different orientations 2 2 3 41 2 3 4( : : : )b b b b for edge detection,fuse together the detected edges to get the image edge 2E . 4. The Results and Analysis of Simulation In order to detect the performance of the algorithm in this paper,first,we add 39。 salt and pepper39。 noise with density of into the images of Flower,Bottle,Man,Watch and we use the traditional operators of edge detection (Lobes and Canny),the algorithms in literalness and the algorithm in this paper to detect the edge of the noise detection results are shown in Figures the analysis of simulation results we see that Canny operator and Lobes operator are sensitive to algorithms have certain ability of inhibition for noise in literalness [5] and [13],but the detection results appear jagged edges and miss the edge example, the edge of the Bottle’s neck is discontinuous,the edges of the Man39。 s hand and coat buttons are missed,and the edge of the top of the hat of Lena is missed,etc., The algorithms can make the edges continuous in literalness [11, 12],but the noises are not pletely filtered improved algorithm in this paper can filter out the noise and retain the edge continuous,plete and no jagged xx 科技学院 2020 届本科生毕业设计（论文）外文翻译 7 Figure 1 Edge Detection Results of Flower Image by using Various Algorithms xx 科技学院 2020 届本科生毕业设计（论文）外文翻译 8 Figure 2 Edge Detection Results of Bottle Image by using Various Algorithm xx 科技学院 2020 届本科生毕业设计（论文）外文翻译 9 Through the it can be found that with the same concentration of noise,the improved algorithm in this paper is better than the algorithms in literalness in these two indicators of MSE and the dates of literalness [11, 12] are similar to the dates of this paper,the algorithms cannot filter out noise pletely in literalness [11, 12].In conclusion, the algorithm has a very good effect in visual and objective evaluation aspects in this paper. 5. Conclusion Edge detection is one of the important research topics in image processing and puter vision,and morphology is a more effective method in image morphology,the structural elements of different sizes and shapes have different abilities in maintaining image detail and paper proposes a new algorithm of edge detection based on morphology by improving the existing operators and also proposes a new method about experimental results show that the algorithm can effectively restrain the influence of various noises on the edge detection, can detect the detailed information of image edges,and the detected edges are continuous and algorithm in this paper is superior to the algorithms in the literalness [5, 1113],thus it is more conducive to image analysis and processing. But the theory of mathematics morphology is very rich,and a better method needs to be further research. References： [1] W. HuiDeng. Z. GUILi and L. CiaoMing.“ Research and Application of Edge Detection Operator Based on Mathematical Engineering and . 31.(2020).pp. 223226. [2] X. Duobaa. W. . . Bidin and X. ChiBi.“ Adaptive Algorithm of Edge Detection Based on Mathematical of Computer . 29.(2020).pp. 997999. [3] and . “ Boundary Detection using Mathematical Morphology” .Pattern Recognition . 16.(2020).pp. 12771286. [4] J. Canny.“ A Computational Approach to Edge Detection” .IEEE Transactions on Pattern Analysis and Machine .(2020) . 679698. [5] Z. . . Yuanyuan and L. YongMing.“ An Improved xx 科技学院 2020 届本科生毕业设计（论文）外文翻译 10 Morphological Edge Detection Algorithm of Medical Image, Journal of Chongqing University, vol. 33, (2020), pp. 123126. [6] Z. AuDin.“ A Course of Image Processing and Analysis” .Post Telemuter and .(2020).. [7] L. . Li and Q. Chaos.“ Mathematical Morphology Based Phase Selection Scheme in Digital Relaying”.IEEE C: Ge。