An Adaptive Detection Algorithm for Small Targets in Digital Image
By: Shumei, Wang
.
Contributor(s): Ganesan, Subramaniam.
Publisher: Haryana International Science Press 2016Edition: Vol, 6(2), July-December.Description: 83-87p.Subject(s): Computer EngineeringOnline resources: Click here
In:
International journal of embedded software and open source systemsSummary: The target detection of digital image is one of the main content in computer vision research, which has a wider use. This paper presents an algorithm of the fuzzy small target detection for digital image. First, all the pixel values are looked as a set of elements with the corresponding address, and the small target is determined according to the need, so the image pixels are divided into two sets which includes target set and its complementary set; then the addresses of the storage target pixels are located; the next step to do is calculating the thresholds of target set and its complementary set; Finally, the binarization operation is applied to the small target set and its complement set by the calculated threshold. The test results show that this algorithm for small target detection is very effective.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2021-2022265 |
The target detection of digital image is one of the main content in computer vision research, which has a wider use. This paper presents an algorithm of the fuzzy small target detection for digital image. First, all the pixel values are looked as a set of elements with the corresponding address, and the small target is determined according to the need, so the image pixels are divided into two sets which includes target set and its complementary set; then the addresses of the storage target pixels are located; the next step to do is calculating the thresholds of target set and its complementary set; Finally, the binarization operation is applied to the small target set and its complement set by the calculated threshold. The test results show that this algorithm for small target detection is very effective.
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