The purpose of this paper is to propose a new multi stage algorithm for the recognition of isolated characters. It was similar work done before using only the center of gravity (This paper is extended version of “A f...The purpose of this paper is to propose a new multi stage algorithm for the recognition of isolated characters. It was similar work done before using only the center of gravity (This paper is extended version of “A fast recognition system for isolated printed characters using center of gravity”, LAP LAMBERT Academic Publishing 2011, ISBN: 978-38465-0002-6), but here we add using principal axis in order to make the algorithm rotation invariant. In my previous work which is published in LAP LAMBERT, I face a big problem that when the character is rotated I can’t recognize the character. So this adds constrain on the document to be well oriented but here I use the principal axis in order to unify the orientation of the character set and the characters in the scanned document. The algorithm can be applied for any isolated character such as Latin, Chinese, Japanese, and Arabic characters but it has been applied in this paper for Arabic characters. The approach uses normalized and isolated characters of the same size and extracts an image signature based on the center of gravity of the character after making the character principal axis vertical, and then the system compares these values to a set of signatures for typical characters of the set. The system then provides the closeness of match to all other characters in the set.展开更多
Handwritten signature and character recognition has become challenging research topic due to its numerous applications. In this paper, we proposed a system that has three sub-systems. The three subsystems focus on off...Handwritten signature and character recognition has become challenging research topic due to its numerous applications. In this paper, we proposed a system that has three sub-systems. The three subsystems focus on offline recognition of handwritten English alphabetic characters (uppercase and lowercase), numeric characters (0 - 9) and individual signatures respectively. The system includes several stages like image preprocessing, the post-processing, the segmentation, the detection of the required amount of the character and signature, feature extraction and finally Neural Network recognition. At first, the scanned image is filtered after conversion of the scanned image into a gray image. Then image cropping method is applied to detect the signature. Then an accurate recognition is ensured by post-processing the cropped images. MATLAB has been used to design the system. The subsystems are then tested for several samples and the results are found satisfactory at about 97% success rate. The quality of the image plays a vital role as the images of poor or mediocre quality may lead to unsuccessful recognition and verification.展开更多
Multiuser online system is useful, but the administrator must be nervous at security problem. To solve this problem, the authors propose applying signature verification to multiuser online system. At the authors＇ res...Multiuser online system is useful, but the administrator must be nervous at security problem. To solve this problem, the authors propose applying signature verification to multiuser online system. At the authors＇ research, they attempt adding signature verification function based on DP （Dynamic Programming） matching to existing multiuser online kanji learning system. In this paper, the authors propose the construction of the advance system and methods of signature verification, and evaluate performance of those signature verification methods that difference is combination of using features. From signature verification＇s experimental results, the authors adopted to use writing velocity and writing speed differential as using feature to verify the writer for the system. By using signature database which is construct with 20 genuine signatures and 20 forged signatures with 40 writers and written mostly by English or Chinese literal, experimental results of signature verification records 12.71% as maximum EER （Equal Error Rate）, 6.00% as minimum EER, and 8.22% as average EER. From mentioned above, the authors realized to advance the reliability and usefulness of the multiuser online kanji learning system.展开更多
文摘The purpose of this paper is to propose a new multi stage algorithm for the recognition of isolated characters. It was similar work done before using only the center of gravity (This paper is extended version of “A fast recognition system for isolated printed characters using center of gravity”, LAP LAMBERT Academic Publishing 2011, ISBN: 978-38465-0002-6), but here we add using principal axis in order to make the algorithm rotation invariant. In my previous work which is published in LAP LAMBERT, I face a big problem that when the character is rotated I can’t recognize the character. So this adds constrain on the document to be well oriented but here I use the principal axis in order to unify the orientation of the character set and the characters in the scanned document. The algorithm can be applied for any isolated character such as Latin, Chinese, Japanese, and Arabic characters but it has been applied in this paper for Arabic characters. The approach uses normalized and isolated characters of the same size and extracts an image signature based on the center of gravity of the character after making the character principal axis vertical, and then the system compares these values to a set of signatures for typical characters of the set. The system then provides the closeness of match to all other characters in the set.
文摘Handwritten signature and character recognition has become challenging research topic due to its numerous applications. In this paper, we proposed a system that has three sub-systems. The three subsystems focus on offline recognition of handwritten English alphabetic characters (uppercase and lowercase), numeric characters (0 - 9) and individual signatures respectively. The system includes several stages like image preprocessing, the post-processing, the segmentation, the detection of the required amount of the character and signature, feature extraction and finally Neural Network recognition. At first, the scanned image is filtered after conversion of the scanned image into a gray image. Then image cropping method is applied to detect the signature. Then an accurate recognition is ensured by post-processing the cropped images. MATLAB has been used to design the system. The subsystems are then tested for several samples and the results are found satisfactory at about 97% success rate. The quality of the image plays a vital role as the images of poor or mediocre quality may lead to unsuccessful recognition and verification.
文摘Multiuser online system is useful, but the administrator must be nervous at security problem. To solve this problem, the authors propose applying signature verification to multiuser online system. At the authors＇ research, they attempt adding signature verification function based on DP （Dynamic Programming） matching to existing multiuser online kanji learning system. In this paper, the authors propose the construction of the advance system and methods of signature verification, and evaluate performance of those signature verification methods that difference is combination of using features. From signature verification＇s experimental results, the authors adopted to use writing velocity and writing speed differential as using feature to verify the writer for the system. By using signature database which is construct with 20 genuine signatures and 20 forged signatures with 40 writers and written mostly by English or Chinese literal, experimental results of signature verification records 12.71% as maximum EER （Equal Error Rate）, 6.00% as minimum EER, and 8.22% as average EER. From mentioned above, the authors realized to advance the reliability and usefulness of the multiuser online kanji learning system.
