Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm
At present, the image mining is mainly based on its local and key features, which focuses on its texture and statistical grayscale features, but it focuses on its edge and shape features rarely. However, the contour is also an important feature for image shape recognition. In this paper, a good targ...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/8895000 |
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| _version_ | 1832553266264670208 |
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| author | Siming Meng |
| author_facet | Siming Meng |
| author_sort | Siming Meng |
| collection | DOAJ |
| description | At present, the image mining is mainly based on its local and key features, which focuses on its texture and statistical grayscale features, but it focuses on its edge and shape features rarely. However, the contour is also an important feature for image shape recognition. In this paper, a good target image contour coding algorithm was adopted, and an LCV segmentation model with good image boundary acquisition capability that can reflect the target image contour features was selected for the original image contour segmentation. The detailed features analysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition. |
| format | Article |
| id | doaj-art-731aeb90dd5143dab1c192e53fbef2e8 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-731aeb90dd5143dab1c192e53fbef2e82025-02-03T05:54:26ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/88950008895000Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding AlgorithmSiming Meng0Information Engineering Institute, Guangzhou Railway Polytechnic, Guangzhou 510430, ChinaAt present, the image mining is mainly based on its local and key features, which focuses on its texture and statistical grayscale features, but it focuses on its edge and shape features rarely. However, the contour is also an important feature for image shape recognition. In this paper, a good target image contour coding algorithm was adopted, and an LCV segmentation model with good image boundary acquisition capability that can reflect the target image contour features was selected for the original image contour segmentation. The detailed features analysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition.http://dx.doi.org/10.1155/2020/8895000 |
| spellingShingle | Siming Meng Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm Shock and Vibration |
| title | Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm |
| title_full | Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm |
| title_fullStr | Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm |
| title_full_unstemmed | Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm |
| title_short | Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm |
| title_sort | noise elimination and contour detection based on innovative target image contour coding algorithm |
| url | http://dx.doi.org/10.1155/2020/8895000 |
| work_keys_str_mv | AT simingmeng noiseeliminationandcontourdetectionbasedoninnovativetargetimagecontourcodingalgorithm |