Modified Feature Extraction to apply PSO for solving Handwritten Digits
Jiraphat Samleepant, Chiabwoot Ratanavilisagul · 2023
Handwritten Digit Recognition (HDR) is a widely used technology that has been demonstrated in various research topics. However, there are many limitations because everyone's handwriting is different, including important handwriting characteristics. The experimental results of the previously proposed methods were unsatisfactory when using limited amounts of the datasets for the training model and inefficient pre-processing. Therefore, we describe a new method for increasing the recognition rate through well-planned pre-processing and enhanced feature extraction for applying Particle Swarm Optimization (PSO). When compared to other techniques, the proposed method performed well when tested against an individual's handwritten digits and the original MNIST database. Our results are a high recognition rate and short runtime.