USER'S INSTRUCTIONS: The project work you are about to view is on "Hand written character recognition using deep learning with implementation (matlab)". Please, sit back and study the below research material carefully. This project topic ( Hand written character recognition using deep learning with implementation (matlab) have complete 5(five) Chapters. The complete Project Material/writeup include: Abstract + Introduction + etc + Literature Review + methodology + etc + Conclusion + Recommendation + References/Bibliography.Our aim of providing this "Hand written character recognition using deep learning with implementation (matlab)" project research material is to reduce the stress of moving from one school library to another all in the name of searching for "Hand written character recognition using deep learning with implementation (matlab)" research materials. We are not encouraging any form of plagiarism. This service is legal because, all institutions permit their students to read previous projects, books, articles or papers while developing their own works.
TITLE PAGE
HANDWRITTEN CHARACTER RECOGNITION USING DEEP LEARNING WITH IMPLEMENTATION (MATLAB)
BY
---
--/H2013/01430
DEPARTMENT OF ----
SCHOOL OF ---
INSTITUTE OF ---
DECEMBER,2018
APPROVAL PAGE
This is to certify that the research work, " Hand written character recognition using deep learning with implementation (matlab)" by ---, Reg. No. --/H2007/01430 submitted in partial fulfillment of the requirement award of a Higher National Diploma on --- has been approved.
By
--- . ---
Supervisor Head of Department.
Signature………………. Signature……………….
……………………………….
---
External Invigilator
DEDICATION
This project is dedicated to Almighty God for his protection, kindness, strength over my life throughout the period and also to my --- for his financial support and moral care towards me.Also to my mentor --- for her academic advice she often gives to me. May Almighty God shield them from the peril of this world and bless their entire endeavour Amen.
ACKNOWLEDGEMENT
The successful completion of this project work could not have been a reality without the encouragement of my --- and other people. My immensely appreciation goes to my humble and able supervisor mr. --- for his kindness in supervising this project.
My warmest gratitude goes to my parents for their moral, spiritual and financial support throughout my study in this institution.
My appreciation goes to some of my lecturers among whom are Mr. ---, and Dr. ---. I also recognize the support of some of the staff of --- among whom are: The General Manager, Deputy General manager, the internal Auditor Mr. --- and the ---. Finally, my appreciation goes to my elder sister ---, my lovely friends mercy ---, ---, --- and many others who were quite helpful.
PROJECT DESCRIPTION: This work "
Hand written character recognition using deep learning with implementation (matlab)" research material is a complete and well researched project material strictly for academic purposes, which has been approved by different Lecturers from different higher institutions. We made Preliminary pages, Abstract and Chapter one of "
Hand written character recognition using deep learning with implementation (matlab)" visible for everyone, then the complete material on "
Hand written character recognition using deep learning with implementation (matlab)" is to be ordered for. Happy viewing!!!
To identify a handwritten character is always a challenging task in the field of research on image processing, artificial intelligence as well as machine vision since the handwriting varies from person to person. Moreover, the handwriting styles, sizes and its orientation make it even more complex to interpret the text. The numerous applications of handwritten text in reading bank cheques, Zip Code recognition and in removing the problem of handling documents manually has made it necessary to acquire digitally formatted data. This work is on the recognition of handwritten characters using Matlab, followed by the implementation of various other Matlab toolboxes like Image Processing and Neural Network Toolbox to process the scanned or acquired image. Experimental Results are given to present the proposed model in order to recognize handwritten characters accurately.
TABLE OF CONTENTS
COVER PAGE
TITLE PAGE
APPROVAL PAGE
DEDICATION
ACKNOWELDGEMENT
ABSTRACT
CHAPTER ONE
INTRODUCTION
- BACKGROUND OF THE STUDY
- PROBLEM STATEMENT
- AIM/OBJECTIVE OF THE STUDY
- PURPOSE OF THE STUDY
- RESEARCH QUESTION
- SIGNIFICANCE OF THE STUDY
- SCOPE OF THE STUDY
- LIMITATION OF THE STUDY
- RESEARCH METHODOLOGY
- PROJECT ORGANISATION
CHAPTER TWO
LITERATURE REVIEW
- REVIEW OF THE STUDY
- OVERVIEW OF MACHINE LANGUAGE
- HISTORICAL BACKGROUND OF MACHINE LANGUAGE
- REVIEW OF RELATED STUDIES
- CLASSIFICATION OF HANDWRITING CHARACTER RECOGNITION
CHAPTER THREE
METHODOLOGY
- WORKING PRINCIPLE
- METHOD USED
CHAPTER FOUR
RESULT ANALYSIS
- RESULTS
CHAPTER FIVE
- CONCLUSION
- REFERENCES
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE STUDY
With the advancement of technology, the interfacing between man and machine has increased the scope of research in various domains, thereby making majority of tasks automated and easier to perform.
The development of handwriting recognition systems began in the 1950s when there were human operators whose job was to convert data from various documents into electronic format, making the process quite long and often affected by errors. Automatic text recognition aims at limiting these errors by using image preprocessing techniques that bring increased speed and precision to the entire recognition process. Handwriting recognition has been one of the most fascinating and challenging research areas in field of image processing and pattern recognition in the recent years. It contributes immensely to the advancement of automation process and improves the interface between man and machine in numerous applications.
Over years, organizations get on hold to numerous numbers of handwritten documents, forms and checks. Preserving such paper documents is a very tedious and a time-consuming task. Also over the years these handwritten paper documents might get distorted, and no longer be of use. In order to preserve such handwritten paper documents, if converted to a digital format it would reduce retrieval process and also make handling of such documents easier and reliable.
Optical Character Recognition has been a widely important research topic in pattern recognition, machine vision and artificial learning. Optical Character Recognition is also known as off-line character recognition system.
Optical Character Recognition at times fails to recognize the handwritten text as the writing style varies from person to person. The main task of an Optical Character Recognition is to successfully identify printed text and recognize it. Optical Character Recognition includes the following phases namely, Pre- processing, Segmentation, Feature Extraction and Classification with Recognition. Output of one-phase acts as an input of the next phase in process.
Various novels written by authors are handwritten, these are edited first and then typed to generate a final copy and then printed to produce a book. If a suitable Handwritten Character Recognition System (HCRS) is made available, then these difficulties can be overcome. A HCRS with a high accuracy rate, which can convert any handwritten document to a digital image format, would overcome all anomalies. In some handwritten documents, a common problem faced is to successfully be able to distinguish each and every character successfully. As the writing style of very individual varies, to identity and distinguish them is difficult even for the human eye. At times the same person might not be able to identify the character written by him/her, also he/she might not always write the same character in a similar manner.
The main outcome of a HCRS would be to identify and recognize different handwriting styles. There are various number of ways to write a single character, which differs individual to individual.
This work is on Handwritten Character Recognition using Neural Network in Matlab. MATLAB is one such powerful machine tool where in the availability of Image Acquisition Toolbox, Image Processing Toolbox and Neural Network Toolbox simplifies the task of obtaining and understanding handwritten text.
Hence, the aim is to achieve a high accuracy rate by classifying and recognizing characters to the extent feasible.
1.2 PROBLEM STATEMENT
Handwritten character recognition is a complex problem, which is not easily solvable due to the fact that handwriting varies from person to person. To solve the defined handwritten character recognition problem of classification we used MATLAB computation software with Neural Network Toolbox and Image Processing Toolbox add-on. The purpose is to develop Handwriting Character Recognition Software with a higher accuracy rate reducing its space and time complexities; making it optimal.
- AIM AND OBJECTIVE OF THE STUDY
The main aim of this work is to carry out a study on handwritten character recognition using convolutional neural networks (CNNs) machine language which is implemented using MATLAB. The objectives are:
- The objective of this study is to identify handwritten characters with the use of neural networks
- To use deep learning toolbox to carry out a simulation studies using MATLAB for performance evaluation.
- To reduce retrieval process and also make handling of documents easier and reliable.
1.4 PURPOSE OF THE STUDY
The purpose is to develop Handwriting Character Recognition Software with a higher accuracy rate reducing its space and time complexities; making it optimal
- RESEARCH QUESTION
- What are the advantages of hand written recognition?
- How does handwriting recognition work?
- How can you identify your handwriting using deep learning?
1.6 SIGNIFICANCE OF THE STUDY
The role of Handwriting recognition has led to carrying out this study. Handwriting recognition plays a big role in the technology world now. It also plays an important role in the storage and in the recovery of critical handwriting information. This handwriting recognition ensures an accurate medical care and it also reduces storage costs. It ensures that an essential field of research remains available to students in the future. In this era of globalization, technologies continue to improve and improve more in no time.
1.7 SCOPE OF THE STUDY
Using Matlab Neural Network toolbox, we tried to recognize handwritten characters by projecting them on different sized grids. The first step is image acquisition which acquires the scanned image followed by noise filtering, smoothing and normalization of scanned image, rendering image suitable for segmentation where image is decomposed into sub images. Feature Extraction improves recognition rate and classification. We use character extraction and edge detection algorithm for training the neural network to classify and recognize the handwritten characters.
- LIMITATION OF THE STUDY
As we all know that no human effort to achieve a set of goals goes without difficulties, certain constraints were encountered in the course of carrying out this project and they are as follows:-
- Difficulty in information collection: I found it too difficult in laying hands of useful information regarding this work and this course me to visit different libraries and internet for solution.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet, questionnaire and interview).
- Time Constraint: The researcher will simultaneously engage in this study with other academic work. This consequently will cut down on the time devoted for the research work.
1.9 RESEARCH METHODOLOGY
In the course of carrying this study, numerous sources were used which most of them are by visiting libraries, consulting journal and news papers and online research which Google was the major source that was used.
1.10 PROJECT ORGANISATION
CHAPTER TWO: The chapter one of this work has been displayed above. The complete chapter two of " Hand written character recognition using deep learning with implementation (matlab)" is also available. Order full work to download. Chapter two of " Hand written character recognition using deep learning with implementation (matlab)" consists of the literature review. In this chapter all the related work on " Hand written character recognition using deep learning with implementation (matlab)" was reviewed.
CHAPTER THREE: The complete chapter three of " Hand written character recognition using deep learning with implementation (matlab)" is available. Order full work to download. Chapter three of " Hand written character recognition using deep learning with implementation (matlab)" consists of the methodology. In this chapter all the method used in carrying out this work was discussed.
CHAPTER FOUR: The complete chapter four of " Hand written character recognition using deep learning with implementation (matlab)" is available. Order full work to download. Chapter four of " Hand written character recognition using deep learning with implementation (matlab)" consists of all the test conducted during the work and the result gotten after the whole work
CHAPTER FIVE: The complete chapter five of design and construction of a " Hand written character recognition using deep learning with implementation (matlab)" is available. Order full work to download. Chapter five of " Hand written character recognition using deep learning with implementation (matlab)" consist of conclusion, recommendation and references.
To "DOWNLOAD" the complete material on this particular topic above click "HERE"
Do you want our Bank Accounts? please click HERE
To view other related topics click HERE
To "SUMMIT" new topic(s), develop a new topic OR you did not see your topic on our site but want to confirm the availiability of your topic click HERE
Do you want us to research your new topic? if yes, click "HERE"
Do you have any question concerning our post/services? click HERE for answers to your questions
For more information contact us through any of the following means:
Mobile No 
:+2348146561114 or +2347015391124 [Mr. Innocent]
Email address 
:engr4project@gmail.com
Watsapp No 
:+2348146561114
COUNTRIES THAT FOUND OUR SERVICES USEFUL
Australia, Botswana, Canada, Europe, Ghana, Ireland, India, Kenya, Liberia, Malaysia, Namibia, New Zealand, Nigeria, Pakistan, Philippines, Singapore, Sierra Leone, South Africa, Uganda, United States, United Kindom, Zambia, Zimbabwe, etc
Support: +234 8146561114 or +2347015391124
Watsapp No :+2348146561114
Email Address :engr4project@gmail.com
FOLLOW / VISIT US VIA:
