Image pattern recognition : fundamentals and applications /

This book describes various types of image patterns for image retrieval. All these patterns are texture dependent. Few image patterns such as Improved directional local extrema patterns, Local Quantized Extrema Patterns, Local Color Oppugnant Quantized Extrema Patterns and Local Mesh quantized extre...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Rao, L. Koteswara (Autor), Rahman, Md. Zia Ur (Autor), Rohini, P. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : CRC Press, 2021.
Edición:1st.
Temas:
Optical pattern recognition.
Reconnaissance optique des formes (Informatique)
Optical pattern recognition
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

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100 1 |a Rao, L. Koteswara,  |e author. 
245 1 0 |a Image pattern recognition :  |b fundamentals and applications /  |c L. Koteswara Rao, Md. Zia Ur Rahman, P. Rohini. 
250 |a 1st. 
264 1 |a Boca Raton :  |b CRC Press,  |c 2021. 
300 |a 1 online resource :  |b illustrations (black and white) 
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500 |a 1. INTRODUCTION 1.1 Data Retrieval 1.2 Content Based Image retrieval system 1.3 Organization of Book 2. FEATURES USED FOR IMAGE RETRIEVAL 2.1 Introduction 2.2 Color features 2.3 Texture features 2.4 Local features 2.5 Shape features 2.6 Multiple features 2.7 Problem statement 2.8 Methodology 3. IMPROVED DIRECTIONAL LOCAL EXTREMA <BR>PATTERNS FOR CBIR 3.1 Introduction 3.2 Local patterns 3.3 Directional local extrema Patterns 3.4 Improved directional local extrema patterns 3.5 Conclusion 4. LOCAL QUANTIZED EXTREMA PATTERNS 4.1 Introduction 4.2 Local quantized extrema patterns 4.3 Experimental results and discussion 4.4 Conclusions 5. LOCAL COLOR OPPUGNANT QUANTIZED EXTREMA PATTERNS 5.1 Introduction 5.2 Local color oppugnant quantized extrema patterns 5.3 Experimental results and discussion 5.4 Conclusions 6. LOCAL MESH QUANTIZED EXTREMA PATTERNS 6.1 Introduction 6.2 Local mesh quantized extrema patterns 6.3 Experimental results and discussion 6.4 Conclusions 7. LOCAL PATTERNS FOR FEATURE EXTRACTION 7.1 Quantized Neighborhood Local Intensity Extrema Patterns For Image Retrieval 7.1.1 Major advantages over other methods 7.1.2 Framework of proposed retrieval system 7.1.3 Image Similarity measurement 7.1.4 Experimental results and discussion 7.1.5 Conclusion 7.2 Magnitude Directional Local Extrema Patterns 7.2.1 Introduction 7.2.2 Different types of local patterns 7.2.3 Proposed CMDLEP System 7.2.4 Experimental Results 7.2.5 Conclusion 7.3 Combination of CDLEP and Gabor Features 7.3.1 Introduction 7.3.2 Local Patterns and Variations 7.3.3 Proposed Gabor CDLEP System 7.3.4 Experimental Results 7.3.5 Conclusion 7.4 LEMP: A Robust Image Feature Descriptor for Retrieval Applications 7.4.1 Introduction 7.4.2 Related Local Patterns 7.4.3 Proposed Framework 7.4.4 Conclusion 7.5 Multiple Color Channel Local Extrema Patterns for Image Retrieval 7.5.1 Introduction 7.5.2 Relevant Work 7.5.3 Proposed Method 7.5.4 Experimental Results and Discussions 7.5.5 Conclusion and future scope 7.6 Integration of MDLEP and Gabor Function as a Feature Vector for Image Retrieval System 7.6.1 Introduction 7.6.2 Local Patterns & Variations 7.6.3 Proposed CMDLEP System 7.6.4 Experimental Results 7.6.5 Conclusions 7.7 Local Co-occurrence Patterns 7.7.1 Introduction 7.7.2 Local Patterns 7.7.3 Framework of the proposed system 7.7.4 Experimental Results and Discussions 7.7.5 Conclusion 7.8 Color Based Multi-Directional Local MOTIF XOR Patterns for Image Retrieval 7.8.1 Introduction 7.8.2 Feature Extraction Methods 7.8.3 Proposed Feature Descriptors 7.8.4 Experimental Results and Discussions 7.8.5 Conclusion 7.9 Quantized Local Trio Patterns for Multimedia Image Retrieval System. 7.9.1 Introduction 7.9.2 A Review of local patterns 7.9.3 Proposed Method 7.9.4 Experimental Results and Discussions 7.9.5 Conclusion 8. CONCLUSIONS AND FUTURE SCOPE 8.1 Summary 8.2 Salient features 8.3 Future scope REFERENCES. 
588 |a Description based on CIP data; resource not viewed. 
520 |a This book describes various types of image patterns for image retrieval. All these patterns are texture dependent. Few image patterns such as Improved directional local extrema patterns, Local Quantized Extrema Patterns, Local Color Oppugnant Quantized Extrema Patterns and Local Mesh quantized extrema patterns are presented. Inter-relationships among the pixels of an image are used for feature extraction. In contrast to the existing patterns these patterns focus on local neighborhood of pixels to creates the feature vector. Evaluation metrics such as precision and recall are calculated after testing with standard databases i.e., Corel-1k, Corel-5k and MIT VisTex database. This book serves as a practical guide for students and researchers. -The text introduces two models of Directional local extrema patterns viz., Integration of color and directional local extrema patterns Integration of Gabor features and directional local extrema patterns. -Provides a framework to extract the features using quantization method -Discusses the local quantized extrema collected from two oppugnant color planes -Illustrates the mesh structure with the pixels at alternate positions. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Optical pattern recognition. 
650 6 |a Reconnaissance optique des formes (Informatique) 
650 7 |a Optical pattern recognition  |2 fast 
700 1 |a Rahman, Md. Zia Ur,  |e author. 
700 1 |a Rohini, P.,  |e author. 
776 0 8 |i Print version:  |z 9780367642167 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781000460971/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
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