| Titre : | A Comparative Analysis of special fuzzy clustering algorithm |
| Auteurs : | ELkhensa Ghecham, Auteur ; Fouzia Chighoub, Directeur de thèse |
| Type de document : | Monographie imprimée |
| Editeur : | Biskra [Algérie] : Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie, Université Mohamed Khider, 2022 |
| Format : | 1 vol. (161 p.) / couv. ill. en coul / 30 cm |
| Langues: | Français |
| Sommaire : |
General Introduction …….1 Chapter I. Approaches Segmentation Image 3 I.1. Introduction3 I.2. Definition of an image 3 I.3. Digital picture 3 I.3.1 Characteristics of a digital image 3 I.3.2 pixels 3 I.3.3 The dimension3 I.3.4 The resolution 4 I.3.5 Contrast4 I.3.6 Luminance 4 I.3.7 Noise 5 I.3.8 The histogram 5 I.4. Image types 5 I.4.1 1.5.1. Binary image (black and white) 5 I.4.2 Grayscale (monochrome) image5 I.4.3 Color image (full color) 6 I.5. Image segmentation definition 7 I.6. Applications Domaine 9 I.7. Image Segmentation Approaches 12 I.7.1 Region based approaches.. 13 I.7.2 Contours based approaches 34 I.8. Conclusion37 Chapitre II. Segmentation by fuzzy c-means method 38 II.1. Introduction 38 II.2. fuzzy logic38 II.3. The fuzzy subset theory 39 II.4. Clustering definition. 40 II.5. Fcm algorithm 40 II.6. Fcm algorithm shortcomings 42 II.7. Fcm variants 42 II.7.1 Fuzzy Clustering with Constraints (FCMS) and its Variants 42 II.7.2 C. Enhanced Fuzzy C-Means Clustering (EnFCM). 44 II.7.3 Fast Generalized Fuzzy C-Means Clustering (FGFCM) 46 II.7.4 FUZZY LOCAL INFORMATION C-MEANS (FLICM)CLUSTERING ALGORITHM 47ii The FLICM algorithm is given as follows: 49 II.7.5 Spatial FCM. 49 II.7.6 robust fuzzy c-means with adaptive spatial & intensity constraint and membership linking (FCM_SICM)[52] 50 II.8. Conclusion53 Chapitre III. Design 54 III.1. Introduction 54 III.2. General design 54 III.2.1 Input picture 55 III.2.2 Classification methods 55 III.2.3 labeling 55 III.2.4 Comparison methods . 55 III.3. The detailed design 58 III.3.1 Saving the input image 61 III.3.2 Generation of a new image61 III.3.3 Parameter and input initialization . 65 III.3.4 Calcul des centres et des degrés d'appartenance . 65 III.3.5 The stopping criterion. 65 III.3.6 Labeling 66 III.4. Interface module . 66 III.5. Conclusion 70 Chapitre IV. Implementation 71 IV.1. Introduction 71 IV.2. The work environment 71 IV.3. The coding language. 71 IV.4. Coding software 72 IV.5. Libraries to use 73 IV.6. Machine Features 73 IV.7. Presentation of the application interface 73 IV.8. Evaluation on segmentation results 75 IV.9. The comparison between the algorithms . 89 IV.9.1 Comparison by the Validity Indices functions 89 IV.9.2 Comparison by Entropy-based Objective Evaluation functions 90 IV.9.3 Comparison by the Execution time 92 IV.10. Conclusion 93 General Conclusion . 94 References ……………………………………………………………………………………….….95 |
Disponibilité (1)
| Cote | Support | Localisation | Statut |
|---|---|---|---|
| MINF/703 | Mémoire master | bibliothèque sciences exactes | Consultable |
