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Recognition Impact on Rescaled Handwritten Digit Images Using Support Vector Machine Classification http://wcsit.org/volume-11-issue-1-2021
... For the last decades, Handwritten Digit Recognition (HDR) has been known as one of the main research problems in handwriting recognition systems. HDR can be defined as "the process of trans-forming images of handwritten digits into numeric values in a suitable format for the computer" [1]. Like all handwriting recognition systems, HDR based on Machine Learning techniques is composed of five important stages. ...
Recognition of handwritten digits is a dominant research problem in the field of image analysis and pattern recognition. In particular, feature extraction-based appearance approaches solve many research problems. In this work, we introduce a new method using encryption techniques such as the feature extraction stage. Furthermore, this method is very skilled for handwritten digit recognition as it is less affected by variations in shape and slant. The proposed method is carried in two steps: first, we concatenate the entire image with its encrypted image. Second, the image pixels are collected into a vector. The performance of the proposed approach is evaluated for recognizing the isolated handwritten digits from the CVL dataset. The experimental results showed recognition with high accuracy.
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