Handwritten Digit Recognition based on Output-Independent Multi-Layer Perceptrons
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 6
Abstract
With handwritten digit recognition being an established and significant problem that is facing computer vision and pattern recognition, there has been a great deal of research work that has been undertaken in this area. It is not a trivial task because of the big variation that exists in the writing styles that have been found in the available data. Therefore both, the features and the classifier need to be efficient. The core contribution of this research is the development of a new classification technique that is based on the MLP, which can be identified in handwritten documents as the binary digits ‘0’ and ‘1’. This technique maps the different sets of various input data onto the MLP output neurons. An experimental evaluation of the technique’s performance is provided. This evaluation is based on the well-known ‘Pen-Based Recognition of Handwritten Digits’ dataset, which is comprised of a total of 250 handwriting samples that are taken from 44 writers. The results obtained are very promising for such an approach in accurate handwriting recognition.
Authors and Affiliations
Ismail M. Keshta
Keywords
Related Articles
- EP ID EP259516
- DOI 10.14569/IJACSA.2017.080604
- Views 99
- Downloads 0
Requirement Elicitation Techniques for Open Source Systems: A Review
The trend of Open Source Software development has been increased from the past few years. It has gained much attention of developers in the industry. The development of open source software systems is slightly different...
An Adaptive Hybrid Controller for DBMS Performance Tuning
Performance tuning process of database management system (DBMS) is an expensive, complex and time consuming process to be handled by human experts. A proposed adaptive controller is developed that utilizes a hybrid model...
Hybrid Deep Network and Polar Transformation Features for Static Hand Gesture Recognition in Depth Data
Static hand gesture recognition is an interesting and challenging problem in computer vision. It is considered a significant component of Human Computer Interaction and it has attracted many research efforts from the com...
Effect of Fusion of Statistical and Texture Features on HSI based Leaf Images with Both Dorsal and Ventral Sides
The present work involves statistically analyzing and studying the overall classification accuracy results using Hue channel images of different plant species using their dorsal and ventral sides, and then subjecting the...
A Two-Level Fault-Tolerance Technique for High Performance Computing Applications
Reliability is the biggest concern facing future extreme-scale, high performance computing (HPC) systems. Within the current generation of HPC systems, projections suggest that errors will occur with very high rates in f...