Handwritten Character Recognition on Focused on the Segmentation of Character Prototypes in Small Strips

Abstract

Abstract-The automatic recognition of handwriting is a particularly complex operation. Until now, there is no algorithm able to recognize handwriting without that; there are assumptions to take in advance to facilitate the task of the process. A handwritten text can contain letters lowercase, uppercase letters, characters sticks and digits. Therefore, it is capital to know extract and separate all these different units in order to process them with specific algorithms to their class handwriting.In this paper, we present a system for unconstrained handwritten text recognition, which allows to achieve this operation thanks to an intelligent segmentation based on an iterative cutting in a multi-script environment.The results obtained from the experimental protocol reach an "equal error rate" (EER) neighboring to 6%. These calculations were calculated with a relatively small base; however this same rate can be decreased with great bases. Our results are extremely encouraging for the simple reason that our approach is situated in a more general context unlike other approaches which define several non-rigid assumptions; this clearly makes the problem simpler and may make it trivial.

HWR Text Segmentation Based on Subband Analysis

“…Для изображений текста таким структурированием является сегментация [Hochulia et al, 2018], то есть процесс разделения цифрового изображения на несколько частей. Первым этапом является сегментация текста на строки [Quang Nhat Vo et al, 2018], вторым -сегментация строк на слова [Thontadari, Prabhakar, 2016] и третьим -сегментация слов на символы [Munish et al, 2017;Benafia et al, 2017].…”

A novel method for segmenting and straightening of text lines in handwritten Telugu documents based on smearing and regression approach

“…Touching or overlapping of characters between adjacent lines at single point or multiple point's also frequent problem in handwritten documents. In the literature [1], [42][43][44][45][46][47][48] a lot of Text line segmentation methods were presented which can be broadly divided into seven major categories [1] based on Projection-based methods [12], [37], [38], [40], Smearing methods [20], [42], [42],Grouping methods [7], [15], [16], [29], [39], [41], Methods based on the Hough transform [10], [16], [24], Repulsive-attractive network method [48] , Stochastic method and Processing of overlapping and touching Components. This method well suited for printed documents which contains uniform spacing between text lines but not suitable for unconstrained handwritten documents.…”