There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

A review on image segmentation techniques

In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes contain a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with Shared Information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different level of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems. This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis. Both state-of-the-art works, as well as literature reviews, are welcome for submission. Papers addressing interesting real-world computer vision and multimedia applications are especially encouraged. Topics of interest include, but are not limited to:  • Multi-task learning or transfer learning for large-scale computer vision and multimedia analysis • Deep learning for large-scale computer vision and multimedia analysis • Multi-modal approach for large-scale computer vision and multimedia analysis • Different sharing strategies, e.g., sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, • Real-world computer vision and multimedia applications based on learning with shared information, e.g., event detection, object recognition, object detection, action recognition, human head pose estimation, object tracking, location-based services, semantic indexing. • New datasets and metrics to evaluate the benefit of the proposed sharing ability for the specific computer vision or multimedia problem. • Survey papers regarding the topic of learning with shared information.  Authors who are unsure whether their planned submission is in scope may contact the guest editors prior to the submission deadline with an abstract, in order to receive feedback.

IEEE transactions on pattern analysis and machine intelligence

Review: Digital image steganography: Survey and analysis of current methods

Genetic algorithm-based clustering technique

Many Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching Minutiae are the terminations and bifurcations of the ridge lines in a fingerprint image A gray-scale fingerprint image that has undergone binarization, followed by thinning, in order to extract the minutiae, may contain hundreds of minutiae, all of which are not so vivid and obvious in the original image Thus, the set of minutiae that are well-defined and more prominent than the rest should be given higher relevance and importance in the process of minutiae matching In this work, a gray-scale fingerprint image is first preprocessed to produce a thinned binary image Next, a method to assign a score value to each of the extracted minutiae is proposed, based on certain topographical properties of a minutia The score associated to a minutia signifies its robustness and prominence A minutia with a higher score value should be considered with higher priority in the matching scheme to yield better results Experimental results on several standard databases have been reported

/pdf/determination-of-minutiae-scores-for-fingerprint-image-568gm281l4.pdf

Determination of minutiae scores for fingerprint image applications

Data embedding in digital images involves a trade off relationship among imperceptibility, robustness, data security and embedding rate etc. Genetic Algorithms (GA) can be used to achieve optimal solution in this multidimensional nonlinear problem of conflicting nature. The use of the tool has been explored very little in this topic of research. The current paper attempts to use GA for finding out values of parameters, namely reference amplitude (A) and modulation index (μ) both with linear and non linear transformation functions, for achieving the optimal data imperceptibility. Results on security for the embedded data and robustness against linear, non linear filtering, noise addition, and lossy compression are reported here for some benchmark images.

https://www.isical.ac.in/~malay/Papers/Conf/ICONIP_final.pdf

Genetic Algorithm for Optimal Imperceptibility in Image Communication Through Noisy Channel

This article deals with the fractal based representation of image to perform various image processing tasks like image compression, image magnification and image edge extraction. Representation of an image in terms of a set of affine contractive maps has been regarded as the fractal representation. The set of transformations is called iterative function system (IFS). However, the contribution of the article is based on partitioned iterative function system (PIFS). The basic difference between IFS and PIFS exist in the domain of application of their respective transformation. The cost of generating PIFS code of an image is reduced by using Genetic Algorithms (GAs) based search technique. Image compression is a direct consequence of the PIFS code. On the other hand two other operations, viz, image magnification and edge extraction can also be performed using the PIFS code obtained by the GA based method.

Partitioned Iterative Function System: A New Tool for Digital Imaging

The Euler number is a fundamental topological feature of an image, which remains invariant under translation, rotation, scaling, and rubber-sheet transformation of the image. A novel algorithm for computing the Euler number of a binary image is proposed which is based on the properties of runs of 0's and 1's present in the pixel matrix. The algorithm outperforms significantly the existing techniques in terms of both the number of pixel accesses and CPU time. It can be easily parallelized, and a simple on-chip implementation is reported here. Results on a database consisting of 1039 logo images reveal that the Euler number has a strong discriminatory power, and hence can be used for efficient database searching or matching of binary images. The proposed algorithm is very fast and easy to implement, and has potential of wide applicability in image processing.

On-chip computation of Euler number of a binary image for efficient database search

The proliferation of the digitized media (audio, image and video) introduces a challenging problem of security in data transmission In the network environment In this paper a novel algorithm that serves the purpose of covert image-in-image communication and its VLSI implementation using FPGA is proposed Channel coding and spatial bi-phase modulation scheme are used to map gray-scale image information into a binary equivalent message that extracts message information from the noise less/noisy version of the cover data Implementation of the proposed low cost algorithm may be speeded up significantly by hardware realization and can be used for real time applications of multimedia data transmission VLSI implementation using field programmable gate array (FPGA) has been developed for the algorithms and circuit can be integrated into the existing digital still camera framework

http://www.isical.ac.in/~malay/Papers/Conf/INDICON_2004_303.pdf

Malay K. Kundu

Papers

Determination of minutiae scores for fingerprint image applications

Genetic Algorithm for Optimal Imperceptibility in Image Communication Through Noisy Channel

Partitioned Iterative Function System: A New Tool for Digital Imaging

On-chip computation of Euler number of a binary image for efficient database search

An image-in-image communication scheme and VLSI implementation using FPGA