Character Analysis Using Space in Handwriting Image

Handwriting analysis is an effective and reliable indicator of personality and behaviour. It occurs in several stages. Initially, the handwriting samples are collected on plain paper. For better appearance, pre-processing steps such as binarization and noise removal etc are performed. First step begins with considering colour image or gray scale image as an input, then thresholding converts the image into binary image and noise removal technique is also applied. Then line segmentation, word segmentation and character segmentation are performed. After each segmentation process, normalization techniques are applied for normalization purpose to find out space between lines, words and letters in handwriting images. Finally, the mean of the space between all the closed loops formed by the characters has been found out and compared with the word spaces to determine the character. This paper focuses on efficient method of space analysis in handwritten document. The proposed method based on determination of behaviour based on space analysis. The proposed method was tested on images of IAM database which detect the exact space in between lines, words and characters before and after skew normalization of a document. The experimental result shows that proposed algorithm achieves more than 63% accuracy.