Pattern Recognition Books

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We have compiled the list of Best Reference Books on Pattern Recognition subject. These books are used by students of top universities, institutes and colleges. Here is the full list of best books on Pattern Recognition along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Pattern Recognition subject and came out with a recommended list of best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on “Pattern Recognition” as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

1. “Pattern Recognition and Machine Learning (Information Science and Statistics)” by Christopher M Bishop

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“Pattern Recognition and Machine Learning (Information Science and Statistics)” Book Review: This book describes the pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. Probability distributions are described through graphic models. The book includes an introduction to basic probability theory so it is helpful for first time learners of the subject. It will be useful for postgraduate students studying machine learning in college. The short answer questions and multiple choice questions at the end of each chapter help the students to test their understanding of the subject.

2. “Pattern Recognition: Techniques and Applications” by Rajjan Shinghal

“Pattern Recognition: Techniques and Applications” Book Review: This book provides a comprehensive coverage of the procedures for Pattern Recognition. It begins by introducing the concept of inductive learning. Other important topics such as feature selection and clustering are also included. The last chapter compares the results of classifying a given problem by each procedure, and proposes research on finding their underlying commonality. The book includes programming and non-programming exercises at the end of each chapter for the readers to test their understanding. It will benefit undergraduate and master’s Engineering students for the course on Pattern Recognition. It would also be a useful reference for practicing engineers in industrial and research organizations.

3. “Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition)” by Gernot A Fink

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“Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is a complete guide to markov models in pattern recognition. It includes a detailed description of the EM algorithm. The book also introduces an analysis of efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. A special emphasis is also placed on practical algorithmic solutions. The book covers a description of probability quantities and presents methods for the configuration of hidden Markov models for specific application areas. It is useful for researchers, practitioners, and graduate students of pattern recognition.

4. “NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)” by Ian T Nabney

“NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)” Book Review: This book focuses on describing neural networks and related data modelling techniques. It emphasizes on teaching methods that are relevant to the practical application of neural networks and pattern analysis problems. The book includes examples and demonstration programs to illustrate the theory that helps the reader understand the algorithms and how to apply them. The readers get to learn how to use MATLAB for pattern recognition. The book will benefit teachers and students of undergraduate and postgraduate courses in pattern recognition. The topics are discussed along with examples to give a detailed understanding of the subject.

5. “Pattern Recognition” by Gerhard Rigoll

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“Pattern Recognition” Book Review: This book is a compilation of the proceedings of the 30th Symposium of the German Association for Pattern Recognition. A total of 53 papers cover different topics. The topics are divided into sections to include learning and classification, tracking, medical image processing and segmentation. In addition, audio, speech and handwriting recognition, multiview geometry and 3D-reconstruction, motion and matching, and image analysis are also discussed. The book is a useful learning source for researchers, students and teachers in pattern recognition. It provides technical knowledge of the subject based on real-world applications.

6. “Computer Models of Speech Using Fuzzy Algorithms (Advanced Applications in Pattern Recognition)” by Renato de Mori

“Computer Models of Speech Using Fuzzy Algorithms (Advanced Applications in Pattern Recognition)” Book Review: This book is a detailed study of speech recognition. It looks at fuzzy-set theory and artificial intelligence to find definitive solutions to the speech-recognition problem. The book provides a research analysis of making an experimental model capable of understanding spoken sentences of a natural language. For that purpose, it goes into the complexity of the functions performed by the human brain. The book introduces a method for conceiving modules performing perceptual tasks and for combining them in a speech understanding system. The book is useful for students and teachers of computer science and software engineering. It will also benefit researchers as it includes a thorough research in the field.

7. “A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)” by Makoto Nagao and Takashi Matsuyama

“A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)” Book Review: This book presents a deep unification and synthesis of the two fundamental approaches to pat­tern recognition- numerical (or statistical) and struc­tural (linguistic or syntactic). The methodology adopted by the book is based on natural use of the knowledge-base framework. The structural analysis of complex aerial photographs is achieved through a systematic and practice-oriented approach. The topics are described with illustrations and examples that provide the readers with a practical understanding of the subject matter. The book is useful for practitioners working in the field of advanced systems in pattern recognition. It will also benefit students, teachers and researchers interested in the subject.

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8. “Computational Intelligence in Multi-Feature Visual Pattern Recognition (Studies in Computational Intelligence)” by Pramod Pisharady and Prahlad Vadakkepat

“Computational Intelligence in Multi-Feature Visual Pattern Recognition (Studies in Computational Intelligence)” Book Review: This book presents a collection of computational intelligence algorithms. The focus is on addressing the issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape, etc. In the first part it describes research issues in the field with a survey of the related literature. The next part deals with computational intelligence based algorithms for feature selection and classification. The third part presents biologically inspired algorithms for feature extraction. Several figures, charts, tables and equations helping the reader to understand the material presented without instruction. The book is useful for teachers, students and practitioners in the field of pattern recognition.

9. “Video Text Detection (Advances in Computer Vision and Pattern Recognition)” by Tong Lu and Shivakumara Palaiahnakote

“Video Text Detection (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is designed for the students of computer engineering, researchers and scientists. It discusses the practical applications of video text detection. The topics which are covered in this book are pattern recognition, document analysis, image processing and video retrieval. It also focuses on the techniques for multi-modal analysis and performance evaluation.

10. “Statistical Learning and Pattern Analysis for Image and Video Processing (Advances in Computer Vision and Pattern Recognition)” by Nanning Zheng and Jianru Xue

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“Statistical Learning and Pattern Analysis for Image and Video Processing (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is designed for the students, researchers and scientists. The topics which are image segmentation, stereo matching, object detection and analysis and visual tracking. It discusses the harmonic analysis and partial differential equations. Along with the theoretical portions it also covers the practical applications of video processing. It consists of examples, exercises and questions at the end of the chapter.

11. “Pattern Recognition” by Stefan Roth and Arjan Kuijper

“Pattern Recognition” Book Review: This book covers everything related to pattern recognition from 3D reconstruction, object recognition to medical applications. Over 57 solved papers and 37 posters are included in the book. Some lecture notes are also present in the book.

12. “Image Registration: Principles, Tools and Methods (Advances in Computer Vision and Pattern Recognition)” by A Ardeshir Goshtasby

“Image Registration: Principles, Tools and Methods (Advances in Computer Vision and Pattern Recognition)” Book Review: This book introduces image registration along with its principles, tools and methods. It explains the components of image registration and respective designs of each analysis tools. It includes similarity or dissimilarity measures, point detectors, heterogeneous descriptors and robust estimators. The book contains topics on image resampling, principle axes, optimization and model based methods transformation. There is an appendix on PCA and other glossaries are mentioned in the book.

13. “Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)” by Zheng-Hua Tan

“Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)” Book Review: This book presents the issues in the field of advancement in computing and networking. It is a collection of papers about speech recognition, in particular on mobile and over-the-network systems. It also focuses on automatic speech recognition on mobile devices and over communication networks. The book begins with a comprehensive introduction to the subject of speech recognition in devices and networks. Then it goes on to study speech recognition systems- network, distributed and embedded speech recognition systems. The book is useful for researchers and engineers in the field of speech recognition.

14. “Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)” by imusti

“Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This comprehensive book presents the latest advances in applications of multimedia interaction and user interfaces for consumer electronics. It covers issues of multimedia content analysis and human-machine interaction. The book introduces topics such as novel computationally efficient algorithms to extract semantically meaningful audio-visual events. In addition, it takes into account the cognitive impacts of modality on human information processing and provides an overview on gesture control technologies for CE. The book is useful for researchers and practitioners in multimedia analysis, human-computer interaction and interactive user interfaces. Also useful for graduate students studying computer vision and pattern recognition.

15. “Visual Attributes (Advances in Computer Vision and Pattern Recognition)” by Devi Parikh and Rogerio Schmidt Feris

“Visual Attributes” Book Review: This book provides a detailed overview of the latest advances in machine learning and computer vision related to visual attributes. It highlights how this emerging field intersects with other disciplines, such as computational linguistics and human machine interaction. It explains attribute based methods for zero shot classification, learning using privileged information and methods for multi task attribute learning. It discusses the concept of relative attributes and examines the effectiveness of modeling relative attributes in image search applications and reviews state of the art. Methods for estimation of human attributes and describes their use in a range of different applications are explained. It discusses attempts to build a vocabulary of visual attributes, explores the connections between visual attributes and natural language. It provides contributions from an international selection of world renowned scientists, covering both theoretical aspects and practical applications.

16. “Graph Based Representations in Pattern Recognition” by Edwin Hancock and Mario Vento

“Graph Based Representations in Pattern Recognition” Book Review: This book establishes the refereed procedures of the sixth IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, held in Alicante, Spain in June 2007. The 23 changed full papers and 14 amended banner papers introduced were deliberately surveyed and chosen from 54 entries. The papers are coordinated in effective segments on coordinating, distances and measures, chart based division and picture handling, diagram based grouping, chart portrayals, pyramids, combinatorial guides and homologies, just as chart bunching, implanting and learning.

17. “Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)” by Hong Cheng

“Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is designed for undergraduates, graduates, and research scholars of electrical, electronics. And also for students of embedded systems, computer engineering.This book presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. It describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers. It also discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning. Then includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.

People who are searching for Free downloads of books and free pdf copies of these books on Pattern Recognition – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.

We have created a collection of best reference books on “Pattern Recognition” so that one can readily see the list of top books on “Pattern Recognition” and buy the books either online or offline.

If any more book needs to be added to the list of best books on Pattern Recognition subject, please let us know.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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