Improvement On Triangle Features Based Grouping Features for Offline Digit Handwriting
Keywords:Digit Handwriting, Support Vector Machine, Triangle Geometry, Triangle Features,
AbstractAn offline digit handwriting recognition is one of an active studied that has been explored in the field of pattern recognition. In this paper, an improvement on triangle features based grouping features is proposed. It uses to overcome the problem of processing data where the performance is slow based on time training. This problem occurred due to the huge size of the number of triangle features are used. The grouping features are focused on triangle properties of ratio and gradient where the outcome of this grouping features will produce five triangle features which are gRatio-ABC, gGradient-ABC, angle point A, angle point B and angle point C. Then, the converting process using the absolute value function is applied to increase the classification accuracies for digit dataset of IFCHDB, HODA, MNIST and BANGLA. A classifier of Support Vector Machine was used to measure the accuracies.
How to Cite
TRANSFER OF COPYRIGHT AGREEMENT
The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):
- All proprietary right other than copyright, such as patent rights
- The right to make further copies of all or part of the published article for my use in classroom teaching
- The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
- The right to make copies of the published work for internal distribution within the institution that employs me
I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.