Ebook: Soft Computing for Image Processing

Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the "set algebra" of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc.

---

The volume provides a collection of 21 articles containing new material and describing, in a unified way with extensive real life applications, the merits and significance of performing different image processing/analysis tasks in soft computing paradigm. The articles, written by leading experts all over the world, demonstrate the various ways the fuzzy logic, artificial neural networks, genetic algorithms and fractals can be used independently and in integrated manner to provide efficient and flexible information processing capabilities in a stronger computational paradigm for handling the tasks like filtering, edge detection, segmentation, compression , classification, motion estimation, character regognition and target identification. Application domain includes, among others, data mining, computer vision, pattern recognition and machine learning, information technology, remote sensing, forensic investigation, video abstraction and knowledge based systems.

---

The volume provides a collection of 21 articles containing new material and describing, in a unified way with extensive real life applications, the merits and significance of performing different image processing/analysis tasks in soft computing paradigm. The articles, written by leading experts all over the world, demonstrate the various ways the fuzzy logic, artificial neural networks, genetic algorithms and fractals can be used independently and in integrated manner to provide efficient and flexible information processing capabilities in a stronger computational paradigm for handling the tasks like filtering, edge detection, segmentation, compression , classification, motion estimation, character regognition and target identification. Application domain includes, among others, data mining, computer vision, pattern recognition and machine learning, information technology, remote sensing, forensic investigation, video abstraction and knowledge based systems.
Content:
Front Matter....Pages i-xvii
Soft Computing and Image Analysis: Features, Relevance and Hybridization....Pages 1-20
Front Matter....Pages 21-21
Image Filtering Using Evolutionary Neural Fuzzy Systems....Pages 23-43
Edge Extraction Using Fuzzy Reasoning....Pages 44-78
Image Compression and Edge Extraction Using Fractal Technique and Genetic Algorithm....Pages 79-100
Adaptive Clustering for Efficient Segmentation and Vector Quantization of Images....Pages 101-129
On Fuzzy Thresholding of Remotely Sensed Images....Pages 130-161
Image Compression Using Pixel Neural Networks....Pages 162-182
Genetic Algorithm and Fuzzy Reasoning for Digital Image Compression Using Triangular Plane Patches....Pages 183-204
Compression of Digital Mammograms Using Wavelets and Fuzzy Algorithms for Learning Vector Quantization....Pages 205-245
Soft Computing and Image Analysis....Pages 246-259
Fuzzy Interpretation of Image Data....Pages 260-295
Front Matter....Pages 297-297
New Pattern Recognition Tools Based on Fuzzy Logic for Image Understanding....Pages 299-317
Adaptive, Evolving, Hybrid Connectionist Systems for Image Pattern Recognition....Pages 318-336
Neuro-Fuzzy Computing: Structure, Performance Measure and Applications....Pages 337-374
Knowledge Reuse Mechanisms for Categorizing Related Image Sets....Pages 375-400
Symbolic Data Analysis for Image Processing....Pages 401-428
Front Matter....Pages 429-429
The Use of Artificial Neural Networks for Automatic Target Recognition....Pages 431-472
Hybrid Systems for Facial Analysis and Processing Tasks....Pages 473-506
Handwritten Digit Recognition Using Soft Computing Tools....Pages 507-524
Neural Systems for Motion Analysis: Single Neuron and Network Approaches....Pages 525-551
Back Matter....Pages 583-591
Motion Estimation and Compensation with Neural Fuzzy Systems....Pages 552-582

---

The volume provides a collection of 21 articles containing new material and describing, in a unified way with extensive real life applications, the merits and significance of performing different image processing/analysis tasks in soft computing paradigm. The articles, written by leading experts all over the world, demonstrate the various ways the fuzzy logic, artificial neural networks, genetic algorithms and fractals can be used independently and in integrated manner to provide efficient and flexible information processing capabilities in a stronger computational paradigm for handling the tasks like filtering, edge detection, segmentation, compression , classification, motion estimation, character regognition and target identification. Application domain includes, among others, data mining, computer vision, pattern recognition and machine learning, information technology, remote sensing, forensic investigation, video abstraction and knowledge based systems.
Content:
Front Matter....Pages i-xvii
Soft Computing and Image Analysis: Features, Relevance and Hybridization....Pages 1-20
Front Matter....Pages 21-21
Image Filtering Using Evolutionary Neural Fuzzy Systems....Pages 23-43
Edge Extraction Using Fuzzy Reasoning....Pages 44-78
Image Compression and Edge Extraction Using Fractal Technique and Genetic Algorithm....Pages 79-100
Adaptive Clustering for Efficient Segmentation and Vector Quantization of Images....Pages 101-129
On Fuzzy Thresholding of Remotely Sensed Images....Pages 130-161
Image Compression Using Pixel Neural Networks....Pages 162-182
Genetic Algorithm and Fuzzy Reasoning for Digital Image Compression Using Triangular Plane Patches....Pages 183-204
Compression of Digital Mammograms Using Wavelets and Fuzzy Algorithms for Learning Vector Quantization....Pages 205-245
Soft Computing and Image Analysis....Pages 246-259
Fuzzy Interpretation of Image Data....Pages 260-295
Front Matter....Pages 297-297
New Pattern Recognition Tools Based on Fuzzy Logic for Image Understanding....Pages 299-317
Adaptive, Evolving, Hybrid Connectionist Systems for Image Pattern Recognition....Pages 318-336
Neuro-Fuzzy Computing: Structure, Performance Measure and Applications....Pages 337-374
Knowledge Reuse Mechanisms for Categorizing Related Image Sets....Pages 375-400
Symbolic Data Analysis for Image Processing....Pages 401-428
Front Matter....Pages 429-429
The Use of Artificial Neural Networks for Automatic Target Recognition....Pages 431-472
Hybrid Systems for Facial Analysis and Processing Tasks....Pages 473-506
Handwritten Digit Recognition Using Soft Computing Tools....Pages 507-524
Neural Systems for Motion Analysis: Single Neuron and Network Approaches....Pages 525-551
Back Matter....Pages 583-591
Motion Estimation and Compensation with Neural Fuzzy Systems....Pages 552-582
....