International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 2 (2018) pp. 1155-1164 © Research India Publications. http://www.ripublication.com 1155 A Review of Various Handwriting Recognition Methods Salma Shofia Rosyda 1 and Tito Waluyo Purboyo 2 1,2 Department of Computer Engineering, Faculty of Electrical Engineering, Telkom University, Bandung, West Java, Indonesia ORCIDs : 1 0000-0002-5920-7124, 2 0000-0001-9817-3185 Abstract One of the computer-related problems that are being sought and researched is how an image can be recognized and classified. How computers can recognize images like humans who recognize the image. One that can be recognized from an image is handwriting, handwriting recognition can help with human work such as check analysis and for handwritten form processing. In image recognition, the angle of view, light conditions, and whether the captured image is clear or not will affect the process of recognizing the image. There are several methods to be discussed in this paper, in this paper to be discussed is a method that can be used for handwriting recognition. Keywords: Handwritten method, Image Recognition, Image Classification, INTRODUCTION One of the many computer-related problems that are sought and researched is how images can be recognized and classified. How a picture is recognized as a human who recognizes the image. Image recognition is an important process for image processing [27]. In image recognition, the angle of view, light conditions, and whether the captured image is clear or not will affect the process of recognizing the image [1]. Handwriting recognition is one of the most sought after and studied issues, since handwriting can help humans do some work such as post-exposure, bank check analysis, and handwritten processing on forms. The recognition of images for handwriting is more challenging because each person must have a different handwriting form. In addition to writing handwriting is not always straight sometimes there is a sloping up and there is a downward slant, so handwriting will be more difficult to detect than computer writing that already has a definite form [2]. Handwriting detection definitely has more factors that will influence the successful recognition of a handwriting. Because a misinterpretation will be more handwriting than computer writing that is certain to have a fixed form depending on the type. For handwriting recognition, there are several methods that can be used that will be discussed in the next section. IMAGE RECOGNITION METHODS CONVOLUTIONAL NEURAL NETWORK Convolutional Neural Network (CNN) is one of the most widely used methods for handwriting recognition. Before entering into Convolutional Neural Network the image must go through pre-processing first. The following are the steps of Pre-processing : 1) Input the image you want to recognize [1, 5]. 2) Do cropping or warping. The goal is that the image part that does not want to be recognized is lost [1]. 3) Set the image size. Image size should be all the same [1, 7, 10]. In figure 1 is an example Diagram Recognition of Handwritten [6]. Figure 1: example Diagram Recognition of Handwritten [6]