Recognition of Offline Gujarati Handwritten Disjoint Consonants using Pattern Matching
Arpit A Jain1 , Harshal A Arolkar2, Chirag S Davda3
1Arpit A Jain, Faculty of Computer Technology, GLS University, Ahmedabad, India.
2Harshal A Arolkar, Faculty of Computer Technology, GLS University, Ahmedabad, India.
3Chirag S Davda, Student, GLS University, Ahmedabad, India.
Manuscript received on 12 August 2019. | Revised Manuscript received on 16 August 2019. | Manuscript published on 30 September 2019. | PP: 7849-7851 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6543098319/2019©BEIESP | DOI: 10.35940/ijrte.C6543.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image processing is one of the most popular field nowadays. Recognition of the offline isolated handwritten characters is an area which got lot of attention within the field of Image Processing. Various techniques have been proposed in the area of online and offline handwritten character recognition (HCR). In future HCR is the key factor for the transformation of written or printed text into system understandable format. Thus, providing a boost to digitization era. Gujarati is one such language which has many challenges in creation of an accurate OCR. Researchers have achieved good accuracy in the field of online Gujarati handwritten character recognition. This paper introduces a pattern recognition system which is able to recognize isolated offline Gujarati handwritten characters with higher accuracy. Experiments have been done on sub set of („ગ‟, „ણ‟, „લ‟, „શ‟, „હ‟ ) consonants using a total data set of 6750 handwritten consonants by different individuals. The experimental results achieved a markable contribution in the field of handwritten character recognition.
Keywords: GHCRS Gujarati Handwritten Character Recognition System, Handwritten Character Recognition, OCR, Pattern Recognition.
Scope of the Article: Image Processing and Pattern Recognition