International Research Journal of Engineering and Technology (IRJET) Volume: 09 Issue: 06 | Jun 2022
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e-ISSN: 2395-0056 p-ISSN: 2395-0072
HANDWRITTEN DIGIT RECOGNITION USING MACHINE LEARNING VISHWAJEET KUMAR1, Mr. SK ALTHAF RAHAMAN2 1PG
student, Dept. of Science, GITAM University, Visakhapatnam, India 2Assistant professor, Dept. of Science, GITAM University, Visakhapatnam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract- The task of digitally recognizing handwriting has 2. PROBLEM DEFINITION AND FEASIBILTY been difficult due to the variety of writing styles. Therefore, ANALYSIS we have tried to build a foundation for future research in the area so that researchers can overcome the existing problems. Existing methods and methods of digital recognition manuscripts have been reviewed and understood to analyze the most appropriate and effective digital recognition method. More than 60,000 images were used as photo training sets with a resolution of 28 × 28 pixels. Photos / training sets are matched to a real photo. It was found after a thorough analysis and review that the integrated integration system had a minimum error rate of 0.32%. In this paper, a review of various handwritten digital recognition methods was observed and analyzed.
The world as a whole is working on a variety of machine learning problems. The goal of machine learning is to manipulate and manipulate real-life data and the real-life component of human interaction or complex ideas or real-life problems. What you really want to know about this is the Handwriting Recognition because it is the structure of a certified person and the interaction of categories between other people. 2.1 PROBLEM DEFINITION The goal was to create a suitable algorithm that could deliver the output of a handwritten character by simply taking a picture of that character. When someone asks about image processing it means that the problem cannot be solved because there can be a lot of noise in that photo taken that cannot be controlled by the person. The main thing when a person writes a handwritten letter or digit of our case, he does not have a single idea that he should draw it with broadcast pixels or just like a normal picture given. The machine can do that but not the person. Therefore, by comparing only pixels one can not see that. The concept of machine learning is supervised data. The machine learning algorithm relies entirely on model data. If someone modifies the Image directly, the model will get a lot of flat values because that image can be painted in a variety of RGB formats or with various pixels that can be accurately modeled due to sound. Therefore, in this project one has to build a model by analyzing images and learning by machine. Both methods will be needed because these two methods will improve machine learning and can shape the project.
1. INTRODUCTION The project comes with an OCR (Optical Character Recognition) approach that integrates various aspects of computer science research. The project is to take a picture of a character and process it to see the image of that character as the human brain to see the various digits. This project contains an in-depth picture of the Image Analysis techniques as well as a large machine learning area and machine learning structure called the Neural Network. There are two different parts of the project 1) Training part 2) Evaluation part. Part of the training comes with the idea of training a child by giving different sets of the same characters but not completely different from telling them that the result of this “this”. According to this theory one has to train a newly formed neural network with many characters. This section contains a new algorithm that they created for themselves and was developed according to the need of the project. The test section contains a new database test. This part always comes after the training part. First one has to teach the child how to recognize the character. Then one should check to see if you have given the correct answer or not. If not, one should train him a lot by providing a new database and new entries. As such one should check the algorithm again. There are many parts of modeling and working methods that come to a project that require a lot of mathematical modeling techniques such as optimization and filtering process, how to calculate (How to use neural intermezzo 2 Peter Relents (2016)) and prediction (Kaiming He et al)) after that filter or algorithms come to the background or the result one really needs and finally predict the creation of a predictable model. The machine learning algorithm is made up of concepts of prediction and planning.
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2.2 FEASIBILITY ANALYSIS There is more that can happen. Let's discuss one at a time • Technical Performance: -The software used in this project is open source and one can connect to it whenever he or she wish. The concept of python and open CV another side the The concept of image processing and machine learning is a very popular topic these days. Apart from that the whole working environment of the software Google Colab is open source and can be easily accessed where the internet is. The user can also become an editor and by clicking the start button can set the digit on the webcam screen and see the output.
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