Optimal Threshold Selection Based on Random Fuzzy Sets
Language: English
Published by LAP LAMBERT Academic Publishing Dez 2020, 2020
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 38.62
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This item is printed on demand - it takes 3-4 days longer - Neuware -The extended Canny edge detection technique is proposed to identify the edges efficiently using an automatic selection of optimal threshold values. The proposed work states that the detailed results reveal the superior performance over the traditional canny edge detection algorithm. However proposed algorithm fails for low contrast, multiresolution, and unevenly illuminated images. For the second objective, the gradient profile sharpness (GPS) algorithm is presented to emphasize the impact of illumination contrast on human visual perception. GPS is an edge sharpness metric, used for the description of various kinds of gradient profiles. This method focuses on the enhancement of low-resolution images using the triangle model and further the k-mean clustering is applied for object identification. However, it fails with multiresolution, and unevenly illuminated images. Finally, an optimal local thresholding technique based on random fuzzy sets and entropy measures is presented in this book for segmenting multiresolution and unevenly illuminated images. The results are shown in the form of tables and graphs for three methods. 128 pp. Englisch.…
Seller Inventory # 9786203195743
- Title
- Optimal Threshold Selection Based on Random Fuzzy Sets
- Author
- R. Pradeep Kumar Reddy
- Publisher
- LAP LAMBERT Academic Publishing Dez 2020
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 620319574X
- ISBN 13
- 9786203195743
- Item weight
- 209 grams
- Dimensions
- 220x150x8 mm
"Synopsis" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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