 |
6 books on Handwriting Recognition [PDF]
June 02, 2025 | 20 |
These books describe ML and older algorithms for handwriting recognition (neural networks, CTC, transformers), pre-processing of handwriting images (filtering, segmentation, feature extraction) and real-world cases: digitization of archives, recognition of questionnaires, checks, notes and medical records.
1. Optical Character Recognition Technologies and Algorithms
2025 by Richard Johnson
This book is mainly about OCR technologies, but also contains a short description of the latest achievements in handwriting recognition. And since handwriting recognition is not in great demand and is not very popular among book authors lately, we have to make do with this. In general, this book explains the unpopularity of the topic - due to the complexity of handwriting recognition and the small amount of data for training, which means poor output quality. But it also offers a solution - a hybrid system of CNN (convolutional neural network) trained on various printed fonts and RNN (recurrent neural network) for recognizing written characters with CTC (connected temporal classifier) - this is a special neural network training algorithm used when the input and output have different lengths and the exact alignment is unknown.
Download PDF
2. Handwriting Recognition: Fundamentals and Applications
2023 by Fouad Sabry
"Handwriting Recognition: Fundamentals and Applications" is an adventure into the world of computers attempting the near-impossible—deciphering human handwriting, with all its loops, flourishes and barely legible quirks. Fouad Sabry explains how technologies like optical scanning, neural networks and deep learning come together in a heroic effort to understand the hastily scribbled notes and signatures that baffle even our friends. From touchscreens to scanned documents, Sabry shows how machines learn to read our writing, providing a blend of theory, practical insights and real-world examples, all while tackling one fundamental question: can we really teach machines to read something we can barely read ourselves?
Download PDF
3. Fundamentals in Handwriting Recognition
2012 by Sebastiano Impedovo
"Fundamentals in Handwriting Recognition" chronicles the journey of a group of researchers who decided, against all odds and popular belief, to study something most thought belonged to an esoteric corner of Pattern Recognition. For years, these pioneers presented their scribbly findings at broad conferences, their work often lost amid grander subjects. Then, as if by some cosmic twist, the world realized the value of understanding messy human script, giving rise to dedicated conferences and gatherings. This book collects the wisdom of these pioneers, drawing from International Workshops that were essentially parties celebrating handwriting—where minds gathered to solve the glorious, untidy puzzle of human written expression.
Download PDF
4. Handwriting Recognition: Soft Computing and Probabilistic Approaches
2012 by Zhi-Qiang Liu, Jin-Hai Cai, Richard Buse
In "Handwriting Recognition: Soft Computing and Probabilistic Approaches," the authors lay bare the struggles, the triumphs and the near-constant bafflement of trying to make machines read the anarchic doodles that we call handwriting. From trying to understand postal codes to converting text into voice (for the convenience of those who simply don’t want to read their own writing), the book reveals that despite countless advancements, computers are still playing catch-up to humans when it comes to reading messy, free-form scribbles. It turns out that the problem lies in just how wonderfully unique everyone’s handwriting is—it's no wonder machines still have a lot to learn.
Download PDF
5. Markov Models for Handwriting Recognition
2012 by
"Markov Models for Handwriting Recognition" invites readers into the probabilistic wonderland of Markov models, where every squiggle, loop and flourish is transformed into a series of mathematical probabilities. With hidden Markov models leading the charge and n-gram models making a guest appearance, the book outlines how these predictive frameworks try their best to guess what on earth a person was trying to write. It covers the basics, then rolls up its sleeves to tackle the hairy complexities of turning unpredictably human scrawls into something a computer might comprehend—because, let’s be honest, even we’re not sure what we wrote half the time.
Download PDF
6. Advances in Handwriting Recognition
1999 by Seong-Whan Lee
"Advances in Handwriting Recognition" is a collection of papers selected from the 6th International Workshop on Frontiers in Handwriting Recognition—a gathering that was probably equal parts enlightening and confusing, given that the subject at hand was the unpredictable art of human scribbling. These papers, having undergone the refinement that comes from people questioning, suggesting and occasionally staring blankly at them, explore the progress made in making machines understand human handwriting. It’s a bit like a group of scientists saying, "Yes, it’s messy, but we’re making progress and here’s how!"
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Optical Character Recognition Technologies and Algorithms
2025 by Richard Johnson
This book is mainly about OCR technologies, but also contains a short description of the latest achievements in handwriting recognition. And since handwriting recognition is not in great demand and is not very popular among book authors lately, we have to make do with this. In general, this book explains the unpopularity of the topic - due to the complexity of handwriting recognition and the small amount of data for training, which means poor output quality. But it also offers a solution - a hybrid system of CNN (convolutional neural network) trained on various printed fonts and RNN (recurrent neural network) for recognizing written characters with CTC (connected temporal classifier) - this is a special neural network training algorithm used when the input and output have different lengths and the exact alignment is unknown.
Download PDF
2. Handwriting Recognition: Fundamentals and Applications
2023 by Fouad Sabry
"Handwriting Recognition: Fundamentals and Applications" is an adventure into the world of computers attempting the near-impossible—deciphering human handwriting, with all its loops, flourishes and barely legible quirks. Fouad Sabry explains how technologies like optical scanning, neural networks and deep learning come together in a heroic effort to understand the hastily scribbled notes and signatures that baffle even our friends. From touchscreens to scanned documents, Sabry shows how machines learn to read our writing, providing a blend of theory, practical insights and real-world examples, all while tackling one fundamental question: can we really teach machines to read something we can barely read ourselves?
Download PDF
3. Fundamentals in Handwriting Recognition
2012 by Sebastiano Impedovo
"Fundamentals in Handwriting Recognition" chronicles the journey of a group of researchers who decided, against all odds and popular belief, to study something most thought belonged to an esoteric corner of Pattern Recognition. For years, these pioneers presented their scribbly findings at broad conferences, their work often lost amid grander subjects. Then, as if by some cosmic twist, the world realized the value of understanding messy human script, giving rise to dedicated conferences and gatherings. This book collects the wisdom of these pioneers, drawing from International Workshops that were essentially parties celebrating handwriting—where minds gathered to solve the glorious, untidy puzzle of human written expression.
Download PDF
4. Handwriting Recognition: Soft Computing and Probabilistic Approaches
2012 by Zhi-Qiang Liu, Jin-Hai Cai, Richard Buse
In "Handwriting Recognition: Soft Computing and Probabilistic Approaches," the authors lay bare the struggles, the triumphs and the near-constant bafflement of trying to make machines read the anarchic doodles that we call handwriting. From trying to understand postal codes to converting text into voice (for the convenience of those who simply don’t want to read their own writing), the book reveals that despite countless advancements, computers are still playing catch-up to humans when it comes to reading messy, free-form scribbles. It turns out that the problem lies in just how wonderfully unique everyone’s handwriting is—it's no wonder machines still have a lot to learn.
Download PDF
5. Markov Models for Handwriting Recognition
2012 by
"Markov Models for Handwriting Recognition" invites readers into the probabilistic wonderland of Markov models, where every squiggle, loop and flourish is transformed into a series of mathematical probabilities. With hidden Markov models leading the charge and n-gram models making a guest appearance, the book outlines how these predictive frameworks try their best to guess what on earth a person was trying to write. It covers the basics, then rolls up its sleeves to tackle the hairy complexities of turning unpredictably human scrawls into something a computer might comprehend—because, let’s be honest, even we’re not sure what we wrote half the time.
Download PDF
6. Advances in Handwriting Recognition
1999 by Seong-Whan Lee
"Advances in Handwriting Recognition" is a collection of papers selected from the 6th International Workshop on Frontiers in Handwriting Recognition—a gathering that was probably equal parts enlightening and confusing, given that the subject at hand was the unpredictable art of human scribbling. These papers, having undergone the refinement that comes from people questioning, suggesting and occasionally staring blankly at them, explore the progress made in making machines understand human handwriting. It’s a bit like a group of scientists saying, "Yes, it’s messy, but we’re making progress and here’s how!"
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
