15,604 research outputs found
Automatic histogram threshold using fuzzy measures
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems involved in finding the minimum of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of the histogram, are defined. Then, using an index of fuzziness, a similarity process is started to find the threshold point. A significant contrast between objects and background is assumed. Previous histogram equalization is used in small contrast images. No prior knowledge of the image is required.info:eu-repo/semantics/publishedVersio
Locally Adaptive Block Thresholding Method with Continuity Constraint
We present an algorithm that enables one to perform locally adaptive block
thresholding, while maintaining image continuity. Images are divided into
sub-images based some standard image attributes and thresholding technique is
employed over the sub-images. The present algorithm makes use of the thresholds
of neighboring sub-images to calculate a range of values. The image continuity
is taken care by choosing the threshold of the sub-image under consideration to
lie within the above range. After examining the average range values for
various sub-image sizes of a variety of images, it was found that the range of
acceptable threshold values is substantially high, justifying our assumption of
exploiting the freedom of range for bringing out local details.Comment: 12 Pages, 4 figures, 1 Tabl
Enhancement of Image Resolution by Binarization
Image segmentation is one of the principal approaches of image processing.
The choice of the most appropriate Binarization algorithm for each case proved
to be a very interesting procedure itself. In this paper, we have done the
comparison study between the various algorithms based on Binarization
algorithms and propose a methodologies for the validation of Binarization
algorithms. In this work we have developed two novel algorithms to determine
threshold values for the pixels value of the gray scale image. The performance
estimation of the algorithm utilizes test images with, the evaluation metrics
for Binarization of textual and synthetic images. We have achieved better
resolution of the image by using the Binarization method of optimum
thresholding techniques.Comment: 5 pages, 8 figure
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