Saad Bin Ahmed - Cursive Script Text Recognition in Natural Scene Images: Arabic Text Complexities

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The complexities of cursive scene text are important to highlight in pursuing possible solutions demonstrated by researchers. The contemporary researchers in natural language processing (NLP) field must thrive premise knowledge that elaborates the complexities of cursive text which further provides help in defining solutions explicitly designed for Arabic scene text recognition systems. This book comprehends the intended researchers who want to have an elementary knowledge of Arabic scene text and all its relevant issues. The successful learning systems start with the assumption that how good features have been evolved from camera-captured text images. The text analysis emphasized essential skills in building reliable systems utilizing expertise by relying on the process with an impetus to recognize provided samples with higher accuracy.

When dynamics of cursive scene text are analyzed with emphasis on Arabic, then it is learned that traditional OCR approaches are not suitable to be applied to this intrinsic text pattern. The variant nature of traditional OCRs does not possess any similarity with the issues related to scene text analysis. The difference between aforementioned systems should clearly understandable by the reader. The detail covering context-based LSTM approaches designed for Arabic scene text recognition systems constituted state-of-the-art solutions which need to be discussed in a comprehensive manner.

This book is a result of all difficulties that are overlooked during proposed research. The rationale behind this effort is to compile all proposed solutions that have been suggested for smooth research activities performed in cursive scene text analysis. It is pertinent to discuss regarding deep learning architecture which believes to be suitable for learning the solutions designed for complex script, appeared in natural image. This book places a clear emphasis on context learning classification methods which are a result of rigorous research performed in scene text analysis.

First and foremost, praises and thanks to Almighty for His showers of blessings throughout this research work and successful completion of writing this book.

Writing a book is harder than someones thought and more rewarding than anyone has ever imagined. None of this would have been possible without precious discussion among groupmates that reflects the flow of contents and overall organization of this book. As a first author of this book, I am grateful to all of those with whom I have had the pleasure to work during this and other related projects. Dr. Muhammad Imran Razzak and Prof. Rubiyah Yusof have provided me extensive personal and professional guidance and taught me a great deal about both scientific research and life in general.

Nobody has been more important to me in the pursuit of this project than the members of my family. I would like to thank my parents, whose love and guidance are with me in whatever I pursue. They are the ultimate role models. Most importantly, I wish to thank my loving and supportive wife, Tayyaba, and my three wonderful children, Aiza, Rameen, and Aleyan, who provide unending inspiration.

At the end, we would like to thank Springer for providing us an opportunity to write this book that could be beneficial for newbie in the field of document image analysis and natural language processing.