Asia International Conference on Modelling & Simulation (2008)
May 13, 2008 to May 15, 2008
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMS.2008.141
As humans, it is easy to recognize numbers, letters, voices, and objects, to name a few. However, making a machine solve these types of problems is a very difficult task. Handwritten digits recognition (HDR) is considered as one of difficult problems in the field of pattern recognition. Hence, evaluating a performance of other algorithms on HDR problem is of great importance. In this study, Particle Swarm Optimization (PSO) based method is exploited to recognize unconstrained handwritten digits. Each class is encoded as a centroid in multidimensional feature space and PSO is employed to probe the optimal position for each centroid. The algorithm evaluates on 5 folds cross validation of handwritten digits data, and the results reveal that PSO gives promising performance and stable behavior in recognizing these digits.
Pattern recognition, handwritten digits recognition problem, Particle Swarm Optimization, Classification, Machine learning.
N. O. Ba-Karait and S. M. Shamsuddin, "Handwritten Digits Recognition Using Particle Swarm Optimization," 2008 Second Asia International Conference on Modeling & Simulation(AMS), Kuala Lumpur, 2008, pp. 615-619.