Handwritten Digit Recognition from Digital Image
Abhishek Mehta1, Ashish Chaturvedi2, Dharmendrasinh Rathod3, Maulik Patel5
1Mr. Abhishek Mehta, Parul Institute of Computer Application, Parul University, Vadodara and Calorx Teachers’’ University, Computer Science Department, Ahmadabad, India.
2Dr. Ashish Chaturvedi, Calorx Teachers’’ University, Computer Science Department, Ahmadabad, India.
3Mr. Dharmendrasinh Rathod, Parul Institute of Computer Application, Parul University, Vadodara, India.
3Mr. Mr. Maulik Patel, Parul Institute of Computer Application, Parul University, Vadodara, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2389-2394 | Volume-8 Issue-12, October 2019. | Retrieval Number: L29851081219/2019©BEIESP | DOI: 10.35940/ijitee.L2985.1081219
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© 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: This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) digit/chratchter. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the digit/characters, such as solid binary characters, skeletons (thinned digit /characters), or gray level sub images of each individual character. Latest research in this area has been able to grown some new methodologies to overcome the complexity of Guajarati digit writing style. The recognition of handwritten digits which are written in proper way to easily readable. The problem is human can write digit in different styles so it is not identified by the computer but the some feature extraction methodologies like end point, junction point; straight lines etc. For features identification and character classification studied different algorithm and technique.
Keywords: Character Features Extraction, Digit Recognition, End Point, Junction Point, Classification of Digit.
Scope of the Article: Classification