Image Enhancement for the Sight Impaired
Jim Wakely and Ramon Menendez
Advisor: Dr. Jim Sennott
People with poor vision often use a video reader to assist them in reading documents. Existing systems magnify image detail but have limited video processing capability. Image enhancement techniques such as histogram modification, high-pass median filtering, thresholding, and frequency domain filtering improve clarity and compensate for these shortcomings. A key problem, however, is to automate these techniques to maximize system ease of use.
In this project, digital images were imported into Matlab. An algorithm
was developed for classifying images by whether they contain text or a
picture. If an image was classified text, then a median filter was applied
to the image to reduce impulse noise. Next, the image's histogram was analyzed,
and an appropriate threshold was computed and applied to the image; this
resulted in a much more readable black and white image. Conversely, if
an image contained a picture, then its histogram was modified by histogram
specification. The resultant picture image contained much improved contrast.
Although not included in the final automation design, frequency domain
techniques could then be applied to the resultant picture image to reduce
any high frequency noise.
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