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OCoLC |
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201107s2020 xx o ||| 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d EBLCP
|d OCLCQ
|d REDDC
|d OCLCO
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|a 9781000228458
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|a 1000228452
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|a (OCoLC)1204141728
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|a TA1638.4
|b .R355 2021
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|a 006.6
|q OCoLC
|2 23/eng/20231120
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|a UAMI
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100 |
1 |
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|a Rajinikanth, Venkatesan.
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245 |
1 |
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|a A Beginner's Guide to Multilevel Image Thresholding
|h [electronic resource].
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260 |
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|a Milton :
|b Taylor & Francis Group,
|c 2020.
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300 |
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|a 1 online resource (119 p.).
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490 |
1 |
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|a Intelligent Signal Processing and Data Analysis Ser.
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500 |
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|a Description based upon print version of record.
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505 |
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|a Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgements -- Author Biographies -- Chapter 1: Introduction -- 1.1. Introduction to Image Enhancement -- 1.2. Importance of Image Enhancement -- 1.3. Introduction to Enhancement Techniques -- 1.3.1. Artifact Removal -- 1.3.2. Filtering -- 1.3.3. Contrast Enrichment -- 1.3.4. Edge Detection -- 1.3.5. Thresholding -- 1.3.6. Smoothening -- 1.4. Recent Advancements -- 1.5. Need for Multilevel Thresholding -- 1.6. Implementation and Evaluation of Thresholding Process -- 1.7. Summary -- References
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|a Chapter 2: Thresholding Approaches -- 2.1. Need for Image Thresholding -- 2.2. Bilevel and Multilevel Threshold -- 2.3. Common Thresholding Methods -- 2.3.1. Otsu's Approach -- 2.3.2. Tsallis Approach -- 2.3.3. Fuzzy-tsallis entropy Approach -- 2.3.4. Shannon's Approach -- 2.3.5. Kapur's Approach -- 2.4. Selection of Thresholding Method -- 2.5. Implementation Issues -- 2.6. Summary -- References -- Chapter 3: Grayscale and RGB-Scale Image Examination -- 3.1. Image Selection -- 3.2. Grayscale and RGB-Scale Image -- 3.3. Complexity due to Image Dimension -- 3.4. Complexity due to Pixel Distribution
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|a 3.5. Implementation Steps -- 3.6. Summary -- References -- Chapter 4: Heuristic-Algorithm-Assisted Thresholding -- 4.1. Thresholding Methods -- 4.2. Limitations in Traditional Thresholding -- 4.3. Need for Heuristic Algorithm -- 4.4. Selection of Heuristic Algorithm -- 4.4.1. Particle Swarm Optimization -- 4.4.2. Bacterial Foraging Optimization -- 4.4.3. Firefly Algorithm -- 4.4.4. Bat Algorithm -- 4.4.5. Cuckoo Search -- 4.4.6. Social Group Optimization -- 4.5. Implementation Steps -- 4.6. Summary -- References -- Chapter 5: Objective Function and Image Quality Measures
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|a 5.1. Introduction to Implementation -- 5.2. Monitoring Parameter -- 5.2.1. Objective Function -- 5.2.2. Single and Multiple Objective Function -- 5.3. Assessment of Thresholding Process -- 5.4. Summary -- References -- Chapter 6: Assessment of Images with Constraints -- 6.1. Selection of Test Images -- 6.2. Abnormalities in Test Images -- 6.3. Test Image Stained with Noise -- 6.3.1. Gaussian Noise -- 6.3.2. Local variance Noise -- 6.3.3. Poisson Noise -- 6.3.4. Salt & pepper Noise -- 6.3.5. Speckle Noise -- 6.4. Impact of Noise in Thresholding Outcome -- 6.5. Summary -- References
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|a Chapter 7: Thresholding of Benchmark Images -- 7.1. Selection of Test Image -- 7.3. Selection of Objective Function -- 7.4. Assessment of Outcome and Comparison -- 7.5. Summary -- References -- Chapter 8: Thresholding of Biomedical Images -- 8.1. Need of Thresholding for Medical Images -- 8.2. Thresholding for MRI -- 8.3. Thresholding for Ultrasound Image -- 8.4. Thresholding for RGB-Scale Medical Images -- 8.5. Thresholding of Lung CT Scan Slice Infected With Covid-19 -- 8.6. Summary -- References -- Index
|
590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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0 |
|a Image segmentation.
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650 |
|
6 |
|a Segmentation d'image.
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700 |
1 |
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|a Madhava Raja, Nadaradjane Sri.
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700 |
1 |
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|a Dey, Nilanjan.
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776 |
0 |
8 |
|i Print version:
|a Rajinikanth, Venkatesan
|t A Beginner's Guide to Multilevel Image Thresholding
|d Milton : Taylor & Francis Group,c2020
|z 9780367503147
|
830 |
|
0 |
|a Intelligent Signal Processing and Data Analysis Ser.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6379045
|z Texto completo
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938 |
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|a ProQuest Ebook Central
|b EBLB
|n EBL6379045
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994 |
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|a 92
|b IZTAP
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