Pattern recognition and image processing

This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant. Object analysis first uses image processing to detect objects and extract their features, then identifies and classifies them by pattern recognition. Its manifold applications include recognition of objects in satellite images which enable discrimination between different objects, such as fishing boats, merchant ships or warships; machine spare parts e.g. screws, nuts etc. (engineering); detection of cancers, ulcers, tumours and so on (medicine); and recognition of soil particles of different types (agriculture or soil mechanics in civil engineering).* Outlines the identification and classification of objects by electronics-driven image processing and pattern recognition * Discusses object detection, shape, roundness and sharpness analysis, orientation analysis and arrangement analysis * Delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science and medical imaging From industrial and teaching experience the authors provide a blend of theory and practice of digital signal processing (DSP) for advanced undergraduate and post-graduate engineers reading electronics. This fast-moving, developing area is driven by the information technology revolution. It is a source book in research and development for embedded system design engineers, designers in real-time computing, and applied mathematicians who apph DSP techniques in telecommunications, aerospace (control systems), satellite communications, instrumentation, and medical technology (ultrasound and magnetic resonance imaging).

The book is particularly useful at the hardware end of DSP, with its emphasis on practical I)SP devices and the integration of basic processes with appropriate software. It is unique to find in one volume the implementation of the equations as algorithms, not only in \IATLAB but right up to a working DSP-based scheme. Other relevant architectural features include number representations, multiply-accumulate, special addressing modes, zero overhead iteration schemes. and single and multiple nlicroprocessors which will allow the readers to compare and understand both current processors and future DSP developments.

Fundamental signal processing procedures are introduced and developed: also convolution. correlation, the Discrete Fourier Transform and its fast computation algorithms. Then follo finite impulse response (FIR) filters, infinite impulse response (IlR) filters, multirate filters, adaptive filters, and topics from communication and control. I)esign examples are given in all of these cases, taken through an algorithm testing stage using MATLAB. The design of the latter. using C language models, is explained together with the experimental results of real time integer implementations.

Academic prerequisites are first and second year university mathematics, an introductor knowledge of circuit theor ‘and microprocessors. and C Language.

• Provides an unusual blend of theory and practice of digital signal processing (DSP)
• Discusses fundamental signal processing procedures, convolution, correlation, the Discrete Fourier Transform and its fast computation algorithms
• Includes number representations, multiply-accumulate, special addressing modes, zero overhead iteration schemes, and single and multiple instructions

This text deals with signal processing as an important aspect of electronic communications in its role of transmitting information, and the language of its expression. It develops the required mathematics in an interesting and informative way, leading to confidence on the part of the reader. The first part of the book focuses on continuous-time models, and contains chapters on signals and linear systems, and on system responses. Fourier methods, so vital in the study of information theory, are developed prior to a discussion of methods for the design of analogue filters. The second part of the book is directed towards discrete-time signals and systems. There is full development of the z- and discrete Fourier transforms to support the chapter on digital filter design.

All preceding material in the book is drawn together in the final chapter on some important aspects of speech processing which provides an up-to-date example of the use of the theory. Topics considered include a speech production model, linear predictive filters, lattice filters and cepstral analysis, with application to recognition of non-nasal voiced speech and formant estimation.

In addition to course requirement for undergraduates studying electrical engineering, applied mathematics, and branches of computer science involving such signal processing as speak synthesis, computer vision and robotics, this book should provide a valuable reference source for post-graduate research work in industry and academia.

An elementary knowledge of algebra (e.g. partial fractions) is a prerequisite, and also calculus including differential equations. A knowledge of complex numbers and of the basic concept of a function of a complex variable is also needed.

• Deals with signal processing as an important aspect of electronic communications in its role of transmitting information, and the language of its expression
• Topics considered include a speech production model, linear predictive filters, lattice filters and cepstral analysis, with application to recognition of non-nasal voiced speech and formant estimation

From industrial and teaching experience the authors provide a blend of theory and practice of digital signal processing (DSP) for advanced undergraduate and post-graduate engineers reading electronics. This fast-moving, developing area is driven by the information technology revolution. It is a source book in research and development for embedded system design engineers, designers in real-time computing, and applied mathematicians who apph DSP techniques in telecommunications, aerospace (control systems), satellite communications, instrumentation, and medical technology (ultrasound and magnetic resonance imaging). The book is particularly useful at the hardware end of DSP, with its emphasis on practical I)SP devices and the integration of basic processes with appropriate software. It is unique to find in one volume the implementation of the equations as algorithms, not only in \IATLAB but right up to a working DSP-based scheme. Other relevant architectural features include number representations, multiply-accumulate, special addressing modes, zero overhead iteration schemes. and single and multiple nlicroprocessors which will allow the readers to compare and understand both current processors and future DSP developments. Fundamental signal processing procedures are introduced and developed: also convolution. correlation, the Discrete Fourier Transform and its fast computation algorithms. Then follo finite impulse response (FIR) filters, infinite impulse response (IlR) filters, multirate filters, adaptive filters, and topics from communication and control. I) Design examples are given in all of these cases, taken through an algorithm testing stage using MATLAB. The design of the latter. using C language models, is explained together with the experimental results of real time integer implementations. Academic prerequisites are first and second year university mathematics, an introductor knowledge of circuit theor and microprocessors. and C Language. This text deals with signal processing as an important aspect of electronic communications in its role of transmitting information, and the language of its expression. It develops the required mathematics in an interesting and informative way, leading to confidence on the part of the reader. The first part of the book focuses on continuous-time models, and contains chapters on signals and linear systems, and on system responses. Fourier methods, so vital in the study of information theory, are developed prior to a discussion of methods for the design of analogue filters. The second part of the book is directed towards discrete-time signals and systems. There is full development of the z- and discrete Fourier transforms to support the chapter on digital filter design. All preceding material in the book is drawn together in the final chapter on some important aspects of speech processing which provides an up-to-date example of the use of the theory. Topics considered include a speech production model, linear predictive filters, lattice filters and cepstral analysis, with application to recognition of non-nasal voiced speech and formant estimation. In addition to course requirement for undergraduates studying electrical engineering, applied mathematics, and branches of computer science involving such signal processing as speak synthesis, computer vision and robotics, this book should provide a valuable reference source for post-graduate research work in industry and academia. An elementary knowledge of algebra (e.g. partial fractions) is a prerequisite, and also calculus including differential equations. A knowledge of complex numbers and of the basic concept of a function of a complex variable is also needed. This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant. Object analysis first uses image processing to detect objects and extract their features, then identifies and classifies them by pattern recognition. Its manifold applications include recognition of objects in satellite images which enable discrimination between different objects, such as fishing boats, merchant ships or warships; machine spare parts e.g. screws, nuts etc. (engineering); detection of cancers, ulcers, tumours and so on (medicine); and recognition of soil particles of different types (agriculture or soil mechanics in civil engineering).

• Outlines the identification and classification of objects by electronics-driven image processing and pattern recognition
• Discusses object detection, shape, roundness and sharpness analysis, orientation analysis and arrangement analysis
• Delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science and medical imaging

"From industrial and teaching experience the authors provide a blend of theory and practice of digital signal processing (DSP) for advanced undergraduate and post-graduate engineers reading electronics. This fast-moving, developing area is driven by the information technology revolution. It is a source book in research and development for embedded system design engineers, designers in real-time computing, and applied mathematicians who apply DSP techniques in telecommunications, aerospace (control systems), satellite communications, instrumentation, and medical technology (ultrasound and magnetic resonance imaging)."--BOOK JACKET. "Readership: Advanced undergraduate and post-graduate electronic and telecommunications engineers in academia and industry, computing scientists and applied mathematicians."--BOOK JACKET Reinforced with appropriate software, this introduction to modern methods in the developing field of Digital Signal Processing (DSP) delivers a course text for primarily post-graduates reading areas in electrical engineering, control engineering, communication systems engineering, engineering mathematics and computer science. Its emphasis on current programming practices is an attractive feature to engineers and industrial researchers for whom DSP has important applications. The focus of the book is on the design of digital algorithms and the processing of digital signals in different areas of communications and control and provides the reader with a comprehensive introduction to the underlying principles and mathematical models used to analyse and process different types of digital signals. A R&D source book for design engineers of embedded systems in real-time computing, and applied mathematicians who apply DSP techniques in telecommunications, aerospace (control systems), satellite communications, instrumentation, and medical technology (ultrasound and magnetic resonance imaging). This text for advanced undergraduates reading electrical engineering, applied mathematics, and branches of computer science involved with signal processing (speech synthesis, computer vision and robotics) also serves as a reference source in academia and industry. This work delivers the necessary mathematical and computational background for some processing techniques used for Digital Signal Processing (DSP). Emphasis is placed upon software solutions for which source code is provided.