Consistent relaxation matching for handwritten Chinese character recognition

Due to the complexity in structure and the various distortions (translation, rotation, shifting, and deformation) in different writing styles of Handwritten Chinese Characters(HCCs), it is more suitable to use a structural matching algorithm for computer recognition of HCC. Relaxation matching is a powerful technique which can tolerate considerable distortion. However, most relaxation techniques so far developed for Handwritten Chinese Character Recognition (HCCR) are based on a probabilistic relaxation scheme. In this paper, based on local constraint of relaxation labelling and optimization theory, we apply a new relaxation matching technique to handwritten character recognition. From the properties of the compatibility constraints, several rules are devised to guide the design of the compatibility function, which plays an important role in the relaxation process. By parallel use of local contextual information of geometric relaxationship among strokes of two characters, the ambiguity between them can be relaxed iteratively to achieve optimal consistent matching.published_or_final_versio

Off-line hand-printed chinese character recognition based on stroke matching

The specific purpose of this thesis is the automated recognition of the off-line Chinese hand-printed characters by using a blue ball-point pen. Through mask processing, the main components in a Chinese character such as vertical, horizontal, and slant strokes can be extracted. Then, the connected components with the coordinates of the top, bottom, leftmost, and rightmost ends of each stroke extracted are found. From these coordinates, the length and position of each stroke can be computed. According to the number, relative length, and relative position of each stroke, both of the coarse and fine rule-based classification can be made, and the goal of this thesis is able to be reached. Excluding the load and segmentation of the original image, the computing time for the feature extraction and classification depends on the image size and the number of strokes. It is about 0.3 seconds per Chinese character on an IBM PC 80486 DX33. The advantages of the proposed method include efficient time complexity, strong ability to detect very similar Chinese characters, tolerance of the slope of the stroke, and 96% or higher recognition rate. The disadvantage is the inflexibility for learning driven by the users since the matching rules are open to the manufactures only at present

Feature Extraction Methods for Character Recognition

Not Include

Adaptive pattern recognition of hand-written Chinese characters using Fourier transforms of projection profiles

None provided

Advances in Character Recognition

This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

Character Recognition

Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field