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Segmentation of Cursive Textual Images (Applied to Urdu Script) is designed for students perusing the subject at both undergraduate and postgraduate levels. Features: - Enable students to see how algorithms like artificial neural network (ANN), hidden Markov Model (HMMs) etc. work. - Enable them to understand images, various operations on images and algorithms. - Explain the various implementations of HMMs on values and images. - Includes step-by-step instructions to apply algorithms to solve multi-dimensional problems. - It explains textual images (using Urdu script as example), its cursive nature and difficulties for a computer program to identify characters in textual image. - It also explains glyph or connected component analysis. - It explains ANN algorithm and how it can solve segmentation/recognition of holistic images. - It explains how HMMs is used for the segmentation of Urdu text at character level. - It also explains the mathematical equations involved in HMMs. - It also discussed the limitations of algorithm using bounding box, ANN and HMMs. - Includes comprehensive appendix and important tables, graphs and mathematical equations.
About the author
Shahid Abid is an avid educationist who has been teaching / working with machine learning, artificial intelligence, digital image processing and computer vision for last 14 years.
