Braille image recognition for beginners / Nor Azrin Tarmizi

Tarmizi, Nor Azrin (2017) Braille image recognition for beginners / Nor Azrin Tarmizi. Degree thesis, Universiti Teknologi MARA, Melaka.

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Abstract

Braille can be known as a tactile that consist of dots that is used by visually impaired people in reading and to communicate. However, braille text is a complicated tools that is not easily read by normal people. Braille pattern of each alphabets consists of its own pattern in which some of it does not relate to its alphabet. Thus, it is difficult for normal user to detect and recognize the braille pattern. Hence, the objective of this study is to design and develop a prototype that can translate braille image pattern into readable English text using image processing. In order to recognize the braille image, Bag of Features (BOF) is used for the recognition. BOF consists of Speeded-up Robust Features (SURF) and K-means Clustering. SURF technique determines and generates the features point description of each alphabet whereas K-means Clustering is to get the clusters of words in which it selects the most closer to its image. Additionally, image classification is done where it determines the alphabet of braille image using linear SVM classifier. In this study, 78 of braille images are collected from the internet. Out of 78 images, 76 images have been tested to produce result that is similar to the expected outcome. It is found that 97.44% of accuracy is achieved for overall testing data. From the result, it can be concluded that this study has meet the expectation where most of the braille images are recognizable.

Item Type: Thesis (Degree)
Creators:
CreatorsEmail
Tarmizi, Nor AzrinUNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Communication of computer science information
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Communication of computer science information

Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Programming. Rule-based programming. Backtrack programming
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Programming. Rule-based programming. Backtrack programming

Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Computer software > Application software
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Computer software > Application software
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Item ID: 21373
Uncontrolled Keywords: Braille; Recognition; Bag of Features (BOF); Speeded-Up Robust Features (SURF); K-Means Clustering
Last Modified: 25 Oct 2018 01:40
Depositing User: Perpustakaan UiTM Cawangan Melaka UiTM Cawangan Melaka
URI: http://ir.uitm.edu.my/id/eprint/21373

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