Off-line cursive script recognition: current advances, comparisons and remaining problems

Abstract

This paper presents detailed review in the field of off-line cursive script recognition. Various methods are analyzed that have been proposed to realize the core of script recognition in a word recognition system. These methods are discussed in view of the two most important properties of such systems: size and nature of the lexicon involved and whether or not a segmentation stage is present. Script recognition techniques are classified into three categories: firstly, segmentation-free methods or holistic approaches, that compare a sequence of observations derived from whole word image with similar references of words in the small lexicon. Secondly, segmentation-based methods, that look for the best match between consecutive sequences of primitive segments and letters of a possible word similar to human-like reading technique, in which secure features found all over the word are used to boot-strap a few candidates for a final evaluation phase; thirdly, hybrid approaches. Additionally, different feature extraction techniques are elaborated in conjunction with the classification process. In this scenario, implications of single and multiple classifiers are also observed. Finally, remaining problems are highlighted along with possible suggestion and strategies to solve them.

Concise analysis of current text automation and watermarking approaches

“…The secret information is encoded through a method that hides the existence of the data. A safe communication in an undetectable way and prevent suspicious writing is the aim of steganography . The actual purpose is not only to hide the information but also to hide data existence .…”

An Efficient Character Segmentation Algorithm for Offline Handwritten Uighur Scripts Based on Grapheme Analysis

“…Where H(j) represents the horizontal projection of S R , and W and L are the worth and height of S R , known as in (2).…”

“…In the existing literature, most of handwriting recognition studies for cursive writings have been devoted to Arabic and Farsi [2][3][4][5][6][7][8][9][10][11][12]. But very less research efforts have been done for Uighur scripts [13][14].…”

Fuzzy ARTMAP Approach for Arabic Writer Identification using Novel Features Fusion

“…Writer's identification is a process of identifying the author's from an unknown script (Saba et al, 2014a;2014b;2012;Mahmood et al, 2017;Nodehi et al, 2014). Automatic writer identification systems could be used in courts of law for documents forensic analysis, in banks to trace check writers, in a medical prescription to identify doctors and so on (Zendehdel and Paim, 2014;Rasool and Khan, 2015).…”