Presented by:
E.Malleswara Rao


Image Segmentation Using Information Bottleneck Method
The purpose of this paper is to introduce new segmentation algorithms using a hard version of the information bottleneck method. The objective of this method is to extract a compact representation of a random variable with minimal loss of mutual information with respect to another variable.
Problem Definition:
Existing system:
New segmentation algorithms using a hard version of the information bottleneck m ....etc

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Plz,
I am working with aco for image segmentation and is unable to work it out. plz help me with the code.

Pratik Hajare ....etc

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hi this is anuragh sir,please send me any topic related to image segmentation using bottleneck method ....etc

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Presented By
N.V.L Deepak & M.Ravi


ABSTRACT:
A novel algorithm for image retrieval is presented in this paper. The basic idea of the new algorithm is that the constituent segments of the images are used to retrieve images within a digital library. Image retrieval using segments is distinctive in that the local features of the image are used to retrieve the image instead of the typically utilized global features. In our algorithm, the given image is first segmented into dominant components and then the featur ....etc

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sir please send ppt , code etc for hairis : automatic image registration through histogram based image segmentation
mail id : [email protected] ....etc

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i need the matlab code for image segmentation ....etc

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Hi,
My name is Stephen Raj Kumar from Chennai, India. I'm doing my M.Tech., Embedded System in Hindustan University, Chennai, and my project work is based on ACO in Image Segmentation (Brain Tumor). I was going through some websites for some informations, and saw your site regarding ACO. Since my project is also based on the same, I kindly request you to help me out in it in finding out the codings for it because as you know its important and urgent.If you have any idea regarding it please let me know about it.

My email id raj.805 ....etc

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final year project documentation on image segmentation using k-mean in java or c++ code... ....etc

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segmentation algorithm for medical image segmentation. The use of the conventional watershed algorithm for medical image analysis is widespread because of its advantages, such as always being able to produce a complete division of the image. However, its drawbacks include over-segmentation and sensitivity to false edges. We address the drawbacks of the conventional watershed algorithm when it is applied to medical images by using k-means clustering to produce a primary segmentation of the image before we apply our improved watershed segmentatio ....etc

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Abstract :
Watershed transformation is a powerful technique that can be efficiently used for image segmentation. Its use
for classifying and grading rice kernels has been discussed followed by its implementation on reconfigurable
devices. In this paper, we implement a watershed based segmentation algorithm on a Virtex-6 platform. The
main contribution of this work is the low execution time and minimal internal hardware resource occupation.
Watershed has been written in C-code and also in Verilog hardware descriptive language. The V ....etc

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