[Mistry* et al., 5(6): June, 2016] ISSN: 2277-9655 IC™ Value: 3.00 Impact Factor: 3.785 http: // www.ijesrt.com © International Journal of Engineering Sciences & Research Technology [199] IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY A REVIEW ON SEGMENTATION TECHNIQUES OF LINES, WORDS AND CHARACTERS ON GUJARATI HANDWRITTEN DOCUMENT USING OCR Nilam Mistry*, Sameer Vashi, Vidhi Patel, Kunal Shah, Denish Rixawapla, Foram Rakholiya, Rakesh Savant * Babu Madhav Institute of Information Technology, Uka Tarsadia University Maliba Campus, Gopal Vidhyanagar, Bardoli, Gujarat, India DOI: 10.5281/zenodo.54779 ABSTRACT OCR is technique to convert the handwritten or printed document into the digital format by scanning it which can be understandable by a computer. OCR is important and challenging task in many computer vision applications. Segmentation is generally the first stage in any attempt to analyse or interpret an image automatically. Segmentation is separate the document into lines, lines to words and words to characters which has been one of the major laboriousness in handwritten text recognition. The role of segmentation is a crucial in most tasks requiring image analysis. The success or failure of a task is often a direct consequence of the success or failure of segmentation. Handwritten text documents contain text in free flow manner, also writing style of users may different even sometimes same user’s handwriting are different in different time. That is why segmentation is difficult in case of handwritten text document. As this paper focuses on Gujarati language, it contains more curves, overlapping character & slopes. So, it is very difficult to do segmentation on it. In this paper we have applied some of the segmentation techniques to segment the handwritten Guajarati documents & reached to some conclusion. KEYWORDS: OCR, Connected Components, Gujarati Script, Segmentation. INTRODUCTION OCR stands for optical character recognition. It is the popular technique in digital image processing. In document processing, Image processing and pattern recognition, OCR is the most challenging research field. In computerization of any language, one of the vital tasks is to develop an efficient and effective OCR system for the respected language. Figure 1. Block diagram of OCR