Computational Intelligence in Multi-Feature Visual Pattern Recognition

Hand Posture and Face Recognition using Biologically Inspired Approaches

Автор: Pramod Kumar Pisharady, Prahlad Vadakkepat, Ai Poh Loh

Език:

Корици: С меки корици

Издател: Springer Verlag, Singapore

Наличност: Външен склад

Изпращаме след 5-8 дни

105.19 € 205.74 лв

This book presents a collection of computational intelligence algorithms that addresses issues in vi...

Информация за книгата

Автор

Pramod Kumar Pisharady, Prahlad Vadakkepat, Ai Poh Loh

Език

Английски език

Корици

Книга - С меки корици

Издадена

2016

страници

138

EAN

9789811011719

ISBN

9811011710

Enbook ID

15234284

Издател

Springer Verlag, Singapore

Теглоt

2467

Размери

155 x 235 x 9

Пълно описание

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition. The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

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