Yoruba Handwriting Word Recognition Quality Evaluation of Preprocessing Attributes using Information Theory Approach

Abstract

This paper presents an approach to evaluate the quality of handwritten words using the set of features in the preprocessing stages. This is to determine the effect of various stages of preprocessing of the recognition of Yoruba handwritten characters. We demonstrate our methods using handwritten words samples of the domain of Yoruba medical terminology collected from indigenous Yoruba literate writers. Samples were digitized at 300dpi to facilitate much detail representation of the image dataset. We study the impact of entropy measure for an intuitive interpretation of the analysis of the handwritten words. From the experiment carried out, it was observed that the entropy measure of handwritten word is higher than the typewritten word. This implies that the Information content of the handwritten word is affected by perturbations which need to be removed using appropriate image preprocessing tools to obtain low entropy measure which implies same information content as the original. General TermsPattern Recognition, Handwritten word recognition, Image preprocessing and Information Theory.

Development of an Improved Database for Yoruba Handwritten Character

“…While sub-databases containing characters have also been created, the dataset used is also limited to only five characters. A dataset collected from indigenous writers was also produced [17], in which handwritten Yoruba words were retrieved. By converting RGB to greyscale, binarization, eliminating noise, normalizing, and performing skew correction, these words were scanned and then processed.…”

Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier

“…Yoruba is a native language spoken by over 40 million people in Nigeria and its diaspora [22]. Yoruba alphabets are tonal, which makes its recognition more difficult than that of printed English alphabet [5], [20], [23]. The Yoruba orthography is represented in Table 1.…”

“…Despite, the intensive research on Latin languages, only a few works have been done in the area of indigenous languages [6], [8], [23]. Researchers in handwriting recognition have been considering recognition in different languages as a dissimilar *) Correspondence author (Jumoke Falilat Ajao) Email: jumoke.ajao@kwasu.edu.ng Table 1.…”

“…Researchers in handwriting recognition have been considering recognition in different languages as a dissimilar *) Correspondence author (Jumoke Falilat Ajao) Email: jumoke.ajao@kwasu.edu.ng Table 1. The Yoruba orthography [23], [24] High-Tone (Acute sign) Many researchers have used Freeman chain code for extracting features of characters or numerals due to its simplicity and the capability for small memory requirement. K-Nearest Neighbors (KNN) was also used because of its simplicity, reduced training time and good performance.…”