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Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...
Hairong Qi (born 1970) [1] is a Chinese computer scientist known for her work in image processing, computer vision, signal processing, sensor networks, and visual sensor networks. She is Gonzalez Family Professor of Electrical Engineering and Computer Science at the University of Tennessee. [2]
Split and merge segmentation is an image processing technique used to segment an image. The image is successively split into quadrants based on a homogeneity criterion and similar regions are merged to create the segmented result.
According to figures one to four, we can see how homomorphic filtering is used for correcting non-uniform illumination in the image, and the image become clearer than the original. On the other hand, if we apply the high pass filter to the homomorphic filtered image, the edges of the images become sharper and the other areas become dimmer.
In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...
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In most cases in image processing thickening is performed by thinning the background [1] (,) = () where ∪ {\displaystyle \cup } denotes the set-theoretical difference and ⊙ {\displaystyle \odot } denotes the hit-or-miss transform , and B i {\displaystyle B_{i}} is the structural element and X {\displaystyle X} is the image being operated on.
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