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Reseach Article

Morphological Detection in Images

Published on June 2013 by Dharamvir
International Conference on Current Trends in Advanced Computing ICCTAC 2013
Foundation of Computer Science USA
ICCTAC - Number 1
June 2013
Authors: Dharamvir

Dharamvir . Morphological Detection in Images. International Conference on Current Trends in Advanced Computing ICCTAC 2013. ICCTAC, 1 (June 2013), 20-25.

author = { Dharamvir },
title = { Morphological Detection in Images },
journal = { International Conference on Current Trends in Advanced Computing ICCTAC 2013 },
issue_date = { June 2013 },
volume = { ICCTAC },
number = { 1 },
month = { June },
year = { 2013 },
issn = 0975-8887,
pages = { 20-25 },
numpages = 6,
url = { /proceedings/icctac/number1/12265-1307/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 International Conference on Current Trends in Advanced Computing ICCTAC 2013
%A Dharamvir
%T Morphological Detection in Images
%J International Conference on Current Trends in Advanced Computing ICCTAC 2013
%@ 0975-8887
%N 1
%P 20-25
%D 2013
%I International Journal of Computer Applications

In this paper, morphological connected transformation technique is used to detect the background of the image is captured in poor lighting. Here the contrast image enhancement has been carried out by histogram equalization. Histogram equalization is a well known technique where image quality is improved by equally distributing pixel intensity through available grey scale. The histogram of an image represents the relative frequency of occurrence of the various gray levels in the image. This technique for equalizing the histogram gives the best possible dynamic range and strong contrast. So the image is more visible and it is useful in image enhancement techniques. Transforming an image by its cumulative histogram gives an output histogram, which is flat or equalized. These operators proposed through the processing of images with background, these are mostly captured in dim conditions. Detection using geometrical structures and contrast. Development of images captured in dim conditions using histogram equalization technique is proposed.

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Index Terms

Computer Science
Information Sciences


Morphological Detection Histogram Image Capturing