Title:
automatic_image_segement
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Description: In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.
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File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| gray_segement.m | 1389 | 2019-04-24
|
| h_segement.m | 1135 | 2019-04-24 |
