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Issue : April
2009
DOI: DIP042009001
Title: An Image Enhancement System for Feature Recognition
in Electron Magnetic Resonance Tomograms
Authors: P. Alli, Murali C Krishna., and R. Murugesan
Keywords: Electron Magnetic Resonance Images, Adaptive
Filters, Background Subtraction, Optimal Template,
Signal to Noise Ratio, Feature Detection
Abstract:
An image enhancement system is developed for
better recognition of features of interest in electron
magnetic resonance (EMR) tomograms. The system integrates
background subtraction with adaptive optimal template
filtering for better performance. The non zero background,
caused by the accumulation of imaging agent, is initially
removed by background subtraction using bilinear as
well as cubic interpolation techniques. Subsequently,
a local contrast around each pixel is computed using
an optimal template. The size and shape of the optimal
template is determined by the statistical properties
around the pixel of interest. The application system
is developed in C language, and its performance is
evaluated using murine EMR images, acquired from a
continuous wave EMR scanner. Both signal to noise
ratio (SNR) and the edge preserving characteristics
are used as test parameters for the evaluation of
the system. The results show reliable mapping of the
distribution of imaging agents in various organs and
tumors of a mouse. In comparison to simple adaptive
filtering techniques such as the linear least square
error (LLSE) and the minimum mean square error (MMSE)
methods, the system presented in this paper shows
better image enhancement and greater edge preserving
capability.
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Issue : April 2009
DOI: DIP042009002
Title: Algorithm for Watermarking With Retrieval Systems
Authors: Rekha B Venkatapur, Dr. V.D. Mytri, Dr. A.
Damodaram
Keywords: Algorithm, Clustering, Multimedia Messages,
Watermark
Abstract:
In the recent development of digital multimedia
in an entire range of our everyday life has brought
forth two active areas of research, namely, retrieval
systems and watermarking technology. The problem of
associating messages to multimedia content can be
addressed by a watermarking system which embeds the
associated messages into the multimedia content (also
called Works). The major drawback of watermarking
is that the content will be distorted during embedding.
On the other hand, if we assume that the database
is available, the problem can be addressed by a retrieval
system. Although no undesirable distortion is created,
searching in large databases is fundamentally decoct
(also known as the dimensionality curse). In the present
study a novel framework is presented which strikes
a tirade between watermarking and retrieval systems.
The framework avoids the dimensionality curse by introducing
small distortions (watermark) into the multimedia
content. From another perspective, the framework improves
the watermarking performance, marked by signi?cant
reduction in distortion, by introducing searching
ability in the message detection stage. To prove the
concept, we give an algorithm based on the proposed
notion of "clustering by watermarking".
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Issue : April 2009
DOI: DIP042009003
Title: A Region Based Segmentation Approach in Binary
Image Based on Cellular Automata
Authors: Tapas Kumar, IMS Lamba and G. Sahoo
Keywords: Image Segmentation, Cellular Automata, Neighborhood
Operation, Thresholding
Abstract:
-Segmentation of an image is one of the most
difficult processes in the image processing. In this
paper we describe an algorithm for region based image
segmentation of N- dimensional images using cellular
automata. A region-based method usually proceeds as
follows: the image is partitioned into connected regions
by grouping neighboring pixels of similar intensity
levels. Adjacent regions are then merged under some
criterion involving perhaps homogeneity or sharpness
of region boundaries. The Cellular automata paradigm
is considered as a unifying method for image segmentation.
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Issue : April 2009
DOI: DIP042009004
Title: Multiple Image Watermarking in DWT Domain Using
Neural Network
Authors: Brindha .R and Ezhilarasi .M
Keywords:Image Watermarking, Counter Propagation Neural
Network, DWT, Digital Watermarking, Cryptography,
Image Mapping, Neural Network
Abstract:
This paper proposes the formulation of a more
secure image watermarking methodology based on exploitation
of the perpetual capacity of Discrete Wavelet Transforms
(DWT) and reversible compression capability of Counter
Propagation Neural network (CPN). The usefulness of
CPN in mapping watermark images into few bits and
subsequent embedding with the cover images in wavelet
domain is demonstrated. The proposed method exhibits
high security,high capacity and high imperceptibility
features. Low embedding and tracking costs and low
probability of coincidence are making this method
unique among the previously investigated techniques
by various researchers.
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Issue : April 2009
DOI: DIP042009005
Title: A Survey on Image Segmentation Techniques for
Medical Images
Authors: A. Rajendran, Dr.R.Dhanasekaran
Keywords: Medical Imaging, Classification, Deformable
Models, Magnetic Resonance
Imaging
Abstract:
Image segmentation is one of the primary steps
in image analysis for object identification. The main
aim is to recognise homogeneous regions within an
image as distinct and belonging to different objects
Image segmentation plays a crucial role in many medical
imaging applications by automating or facilitating
the delineation of anatomical structures and other
regions of interest. We present herein a critical
appraisal of the current status of semi-automated
and automated methods for the segmentation of anatomical
medical images. We conclude with a discussion on the
future of image segmentation methods in biomedical
research.
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