image segmentation造句
1. A new image segmentation method based on grey relational analysis and fuzzy entropy is presented.
2. A algorithm of image segmentation is proposed based on relative entropy selection thresholding and edge detection.
3. In it, image segmentation plays very important role in the quantity and quality analysis for the medical ultrasound image, and it influences the continuous processing and analysis directly.
4. Image segmentation of micro printing images is the foundation of the line printing quality detection.
5. This paper proposed a genetic clustering image segmentation algorithm on entropy.
6. FCM algorithm used in image segmentation is a course of unsupervised fuzzy clustering followed by demarcating.
7. Image segmentation and object classification are two important topics of digital image processing.
8. Thus, image segmentation algorithm and image visual feature extraction method are briefly introduced at the beginning of this paper.
9. A practical approach of object description after image segmentation to obtain objects' features is introduced in this paper.
10. Image segmentation algorithm procedure, using Prewitt operator implementation Laplacian operator are examples of implementation.
11. The paper presents an algorithm of automatic SAR image segmentation based on minimum error ratio.
12. Source 2 : What threshold image segmentation and contour extraction.
13. Region growing image segmentation method, the effect of a good factory, worth learning!
14. The optimum threshold determined by the theory of image segmentation is to be the crossover point of the fuzzy enhancement, in order to enhance the contrast of image.
15. This paper presents a new method for image segmentation via adaptive thresholding.
16. A range image segmentation algorithm based on tree structure ellipse cluster split is proposed.
17. An image segmentation approach based on watershed translation and graph theory is proposed.
18. The experimental results show that the image segmentation method based on the biology vision model is effective and efficient.
19. Image segmentation experiments based on the color property of objects shows that the model is effective.
20. Toboggan algorithm is an important tool to image segmentation, and the result of image segmentation depends on how to compute the gradient image to a great extent if applying toboggan to it.
21. An improved fuzzy C-means multi-resolution image segmentation algorithm is proposed. The fuzzy membership function of pixel is modified by the adjacent field information in the algorithm.
22. The definition of Centre of Mass and NMI feature is proposed and the principle and methods of Threshold calculation, Image segmentation, Target recognition and tracking are presented.
23. To solve segmentation problem of dynamic images, this paper presents an algorithm of 2-D minimum cross entropy based on genetic algorithm for dynamic image segmentation.
24. The experiments show the approach is a practical and successful method in KIMONO image segmentation.
25. The preprocessing in an automatic fingerprint identification system usually includes five steps:normalization, directional graph computation, image segmentation, filtering and binarization.
26. Image processing is the core of the system. It consists of image pre-processing, treatment of rifling, image segmentation, feature pick-up, defects recognition and texture analysis of rusts.
27. Parametric active contour model incorporating regions information was studied for image segmentation.
28. Before adopting a fuzzy entropy similarity metric, edge detection, image segmentation and segmentation description are accomplished.
29. One algorithm, isoperimetric algorithm based on graph theory is applied and researched on image segmentation.
30. In order to improve the quality of Laplace operator image segmentation at a high real time capability this paper presented a synchronization dimensional structure filter for Laplace operator.
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