دانلود کتاب Integrated region-based image retrieval

"Integrated Region-Based Image Retrieval, presents a wavelet-based approach for feature extraction, combined with integrated region matching. An image in the database, or a portion of an image, is represented by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. A measure for the overall similarity between images is developed as a region-matching scheme that integrates properties of all the regions in the images. The advantage of using this "soft matching" is that it makes the metric robust to poor segmentation, an important property that previous research has not solved.Integrated Region-Based Image Retrieval demonstrates an experimental image retrieval system called Simplicity (Semantics-sensitive Integrated Matching for Picture Libraries). This system validates these methods on various image databases, proving that such methods perform much better and much faster than existing ones. The system is exceptionally robust to image alterations such as intensity variation, sharpness variation, intentional distortions, cropping, shifting, and rotation. These features are extremely important to biomedical image databases since visual features in the query image are not exactly the same as the visual features in the images in the database."."Integrated Region-Based Image Retrieval is an excellent reference for researchers in the fields of image retrieval, multimedia, computer vision and image processing."--BOOK JACKET. Read more... 1. Text-based image retrieval 2 -- 2. Content-based image retrieval 3 -- 3. Applications of CBIR 3 -- 3.1. Biomedical applications 3 -- 3.2. Web-related applications 6 -- 3.3. Other applications 7 -- 4. Summary of our work 7 -- 4.1. Semantics-sensitive image retrieval 8 -- 4.2. Image classification 9 -- 4.3. Integrated Region Matching distance 10 -- 4.4. Applications of the methods 12 -- 2. Content-based image retrieval 17 -- 2.1. Major challenges 18 -- 2.2. Previous work 24 -- 2.3. CBIR for biomedical image databases 33 -- 3. Image semantic classification 34 -- 3.1. Semantic classification for photographs 34 -- 3.2. Medical image classification 36 -- 3. Wavelets 39 -- 2. Fourier transform 40 -- 3. Wavelet transform 41 -- 3.1. Haar wavelet transform 41 -- 3.2. Daubechies' wavelet transform 42 -- 4. Applications of wavelets 46 -- 4. Statistical Clustering and Classification 49 -- 2. Artificial intelligence and machine learning 50 -- 3. Statistical clustering 51 -- 3.1. K-means algorithm 51 -- 3.2. TSVQ algorithm 53 -- 4. Statistical classification 55 -- 4.1. CART algorithm 55 -- 5. Wavelet-Based Image Indexing and Searching 63 -- 2. Preprocessing 64 -- 2.1. Scale normalization 64 -- 2.2. Color space normalization 65 -- 3. Multiresolution indexing 65 -- 3.1. Color layout 66 -- 3.2. Indexing with the Haar wavelet 66 -- 3.3. Overview of WBIIS 67 -- 4. Indexing algorithm 68 -- 5. Matching algorithm 70 -- 5.1. Fully-specified query matching 70 -- 5.2. Partial query 73 -- 6. Performance 75 -- 7. Limitations 83 -- 6. Semantics-Sensitive Integrated Matching 85 -- 3. Image segmentation 86 -- 4. Image classification 90 -- 4.1. Textured vs. non-textured images 90 -- 4.2. Graph vs. photograph images 92 -- 5. Similarity metric 93 -- 5.1. Integrated region matching 93 -- 5.2. Distance between regions 98 -- 6. System for biomedical image databases 101 -- 6.1. Feature extraction 102 -- 6.2. Wavelet-based progressive transmission 102 -- 7. Clustering for large databases 103 -- 7. Image Classification By Image Matching 105 -- 2. Industrial solutions 106 -- 3. Related work in academia 106 -- 4. System for screening objectionable images 107 -- 4.1. Moments 108 -- 4.2. Algorithm 109 -- 4.3. Evaluation 113 -- 5. Classifying objectionable websites 114 -- 5.1. Algorithm 115 -- 5.2. Statistical classification process for websites 116 -- 5.3. Limitations 121 -- 5.4. Evaluation 121 -- 8. Evaluation 123 -- 3. Data sets 124 -- 3.1. COREL data set 124 -- 3.2. Pathology data set 124 -- 4. Query interfaces 125 -- 4.1. Web access interface 125 -- 4.2. JAVA drawing interface 126 -- 4.3. External query interface 127 -- 4.4. Progressive browsing 128 -- 5. Characteristics of IRM 128 -- 6. Accuracy 129 -- 6.1. Picture libraries 131 -- 6.2. Systematic evaluation 136 -- 6.3. Biomedical image databases 144 -- 7. Robustness 145 -- 7.1. Intensity variation 147 -- 7.2. Sharpness variation 148 -- 7.3. Color distortions 148 -- 7.4. Other intentional distortions 149 -- 7.5. Cropping and scaling 150 -- 7.6. Shifting 150 -- 7.7. Rotation 151 -- 8. Speed 152 -- 2. Limitations 160 -- 3. Areas of future work 161