Date of Award

12-2015

Degree Name

Master of Science in Engineering

Department

Electrical and Computer Engineering

First Advisor

Dr. Ikhlas Abdel-Qader

Second Advisor

Dr. Raghvendra Gejji

Third Advisor

Dr. Azim Houshyar

Fourth Advisor

Dr. Osama Abudayyeh

Keywords

FPGA, High Performance Computing, short read alignment, DNA sequencing, Bioinformatics

Access Setting

Masters Thesis-Open Access

Abstract

Persons of visual impairment make up a growing segment of modern society. To cater to the special needs of these individuals, society ought to consider the design of special constructs to enable them to fulfill their daily necessities. This research proposes a new method for text extraction from indoor signage that will help persons of visual impairment maneuver in unfamiliar indoor environments, thus enhancing their independence and quality of life.

In this thesis, images are acquired through a video camera mounted on glasses of the walking person. Frames are then extracted and used in an integrated framework that applies Maximally Stable Extremal Regions (MSER) to detect alphabets along with a morphological dilation operation to identify clusters of alphabets (words). Proposed method has the ability to localize and detect the orientation of these clusters. A rotation transformation is performed when needed to realign the text into a horizontal orientation and allow the objects to be in an acceptable input to any of the available optical character recognition (OCR) systems. Analytical and simulation results verify the validity of the proposed system.

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