Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Ikhlas Abdel-Qader
Dr. Raghvendra Gejji
Dr. Azim Houshyar
Dr. Osama Abudayyeh
FPGA, High Performance Computing, short read alignment, DNA sequencing, Bioinformatics
Masters Thesis-Open Access
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.
Ahmed, "Signage Recognition Based Wayfinding System for the Visually Impaired" (2015). Master's Theses. 649.