# Kannan BalakrishnanCochin University of Science and Technology | CUSAT · Department of Computer Applications

Kannan Balakrishnan

M.sc,M.Phil,M.Tech,PhD

## About

102

Publications

52,992

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1,052

Citations

Citations since 2017

Introduction

Additional affiliations

February 1999 - present

## Publications

Publications (102)

The rise of cultural tourism in India and massive digitization over the last decade has necessitated preserving Indian art forms. Recent advances in artificial intelligence (AI) have provided the tools and techniques to make these efforts more efficient. The potential research areas involved are digital image processing, computer vision, and machin...

Computer Assistive Technologies for Physically and Cognitively Challenged Users focuses on the technologies and devices that assist individuals with physical and cognitive disabilities. These technologies facilitate independent activity and participation, serving to improve daily functional capabilities. The book features nine chapters that cover a...

The median of a graph consists of those vertices which minimize the average distance to all other vertices. It plays an important role in optimization scenarios like facility location problems. Sierpiński graphs are the state graphs of the Switching Tower of Hanoi problem, a variant of the Tower of Hanoi game. They also provide optimum models for i...

Lack of Sign Language-based learning tools is a hindrance in acquiring knowledge for deaf students. Technology-based tools have introduced innovative ways of learning textbook contents. Augmenting textbook contents with sign can significantly help in learning. This paper proposes SignText, a bilingual tool for learning textbook lessons. This web-ba...

Offensive speech identification in social media communication has risen to the top of the priority list for avoiding confrontations and curtailing unwanted behaviour. Hate speech identification becomes difficult in a context, where multilingual speakers fluctuate between various languages, making algorithms built for monolingual corpora inadequate....

In this work, we study the vulnerability of link-weighted networks against different central-attack strategies. We simulate simultaneous and sequential attacks on networks based on three network centralities, viz. degree (DC), betweenness (BC) and closeness (CC) centralities. We observed two network properties, the disintegration of giant component...

Getting to know sign equivalent of a spoken language word is not that easy when accessing a web page. In many cases, people search multimedia sign dictionaries to find the sign equivalent. ISLHelper is a browser plugin that can display Indian Sign Language(ISL) signs within a web page without navigating away from it. Both qualitative and quantitati...

In any network, the interconnection of vertices by means of geodesics and the number of geodesics are important. There exists a class of centrality measures based on the number of geodesics passing through a vertex. Betweenness centrality indicates the betweenness of a vertex or how often a vertex appears on geodesics between other vertices. It has...

In this work, we revisit central attacks in complex networks. We simulate simultaneous as well as sequential attacks on networks based on degree (DC), betweenness (BC) and closeness (CC) centralities. We observed the disintegration of giant components and updates in average geodesic distance, in order to assess the vulnerability of networks. There...

Purpose
Vocabulary learning is a difficult task for children without hearing ability. Absence of enough learning centers and effective learning tools aggravate the problem. Modern technology can be utilized fruitfully to find solutions to the learning difficulties experienced by the deaf. The purpose of this paper is to present SiLearn – a novel te...

We introduce a new centrality measure, known as profile closeness, for complex networks. This network attribute originates from the graph-theoretic analysis of consensus problems. We also demonstrate its relevance in inferring the evolution of network communities.

Sign Language is one of the medium of communication for deaf people. One should learn sign language to interact with them. Learning usually takes place in peer groups. There exist very few study materials for sign learning. Because of this, the process of learning sign language learning is a difficult task. Fingerspelled sign learning is the initia...

Betweenness centrality is a widely used measure in various graphs and it has a pivotal role in the analysis of complex networks. It measures the potential or power of a node to control the communication over the network. The computation is based on the assumption that information primarily flows over the shortest paths between the nodes of the netw...

Reliant components of a network are the connector nodes which aid in establishing a strongly connected network. Betweenness centrality of a node well captures its connecting capability. We suggest some new betweenness centrality measures which could be useful in analysing the structural connectivity of a network. In this paper we study the behaviou...

Availability of a sign language dictionary is very important for the literacy of deaf people. But the intricacies involved in the representation of the sign language impede attempts at representing it in a printed format. A video based solution helps to solve this problem. This article discusses the development of a bilingual mobile sign language d...

In this paper, we introduce a generalized concept of vertex transitivity in graphs called generalized vertex transitivity. We put forward a new invariant called transitivity number of a graph. The value of this invariant in different classes of graphs is explored. Also, different results showing the importance of this concept is established.

A cyber-physical system is often a large and critical infrastructure. For ensuring the reliability of such a system, we should devise advanced security measures. The challenge is thus to ensure security in each and every component of the underlying complex system. Usually, the biggest hurdle here is the huge cost incurred in protecting the entire s...

Reliant components of a network are the connector nodes which aid in establishing a strongly connected network. Betweenness centrality of a node well captures its connecting capability. We suggest some new betweenness centrality measures which could be useful in analysing the structural connectivity of a network. In this paper, we study the behavio...

We study the vulnerability of synthetic as well as real-world networks in center-based attacks. These attacks are node-removal attacks which involve identifying the central node set and removing them from the network.

Various machine learning methods for writer independent recognition of Malayalam handwritten district names are discussed in this paper. Data collected from 56 different writers are used for the experiments. The proposed work can be used for the recognition of district in the address written in Malayalam. Different methods for Dimensionality reduct...

In any network, the interconnection of nodes by means of geodesics and the number of geodesics existing between nodes are important. There exists a class of centrality measures based on the number of geodesics passing through a vertex. Betweenness centrality indicates the betweenness of a vertex or how often a vertex appears on geodesics between ot...

In this work, we present an algorithm for detecting the boundary of binary and grayscale images in the presence of Gaussian noise. We use the recently developed morphological operators on hypergraphs to achieve this task. Opening-closing operations in Mathematical Morphology are the classically and most commonly used preprocessing step in noisy ima...

Betweenness centrality is a widely-used measure in the analysis of large complex networks. It measures the potential or power of a vertex to control the communication over the network under the assumption that information primarily flows over the shortest paths between them. In this paper we prove several results on betweenness centrality of Cartes...

For a set S of vertices and the vertex v in a connected graph G, maxx∈Sd(x,v) is called the S-eccentricity of v in G. The set of vertices with minimum S-eccentricity is called the S-center of G. Any set Aof vertices of G such that A is an S-center for some set S of vertices of G is called a center set. We identify the center sets of certain classes...

Cyber Security is a buzz word in communication and IT world. Our aim is to analyze the present implementation of security policy model in Academic Institutions- Indian Perspective. Also we discussed about the various security models. We found that it is essential to incorporate cyber crimes using institutional networks in policy models. Because of...

The medical imaging technology plays a crucial role in visualization and analysis of the human body with unprecedented accuracy and resolution. Analyzing the multimodal for disease-specific information across patients can reveal important similarities between patients, hence their underlying diseases and potential treatments. Classification of MR b...

In 1952 Sholander formulated an axiomatic characterization of the interval function of a tree with a partial proof. In 2011 Chvátal et al. gave a completion of this proof. In this paper we present a characterization of the interval function of a block graph using axioms on an arbitrary transit function R. From this we deduce two new characterizatio...

There are several centrality measures that have been introduced and studied
for real world networks. They account for the different vertex characteristics
that permit them to be ranked in order of importance in the network.
Betweenness centrality is a measure of the influence of a vertex over the flow
of information between every pair of vertices u...

Sign language, which is a medium of communication for deaf people, uses
manual communication and body language to convey meaning, as opposed to using
sound. This paper presents a prototype Malayalam text to sign language
translation system. The proposed system takes Malayalam text as input and
generates corresponding Sign Language. Output animation...

Handwritten character recognition is still a research challenge in OCR discipline, especially for Indian scripts. This paper deals with handwritten Malayalam, a major Indian script, where past work considered a small subset of characters only. In this paper we deal with complete set of basic characters, vowel and consonant signs and compound charac...

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slic...

Given a graph GG and a set X⊆V(G)X⊆V(G), the relative Wiener index of XX in GG is defined as WX(G)=∑{u,v}∈X2dG(u,v). The graphs GG (of even order) in which for every partition V(G)=V1+V2V(G)=V1+V2 of the vertex set V(G)V(G) such that |V1|=|V2||V1|=|V2| we have WV1(G)=WV2(G)WV1(G)=WV2(G) are called equal opportunity graphs. In this note we prove tha...

The focus of this paper is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of dual adjunctions between the vertex set and the hyperedge set of a hypergraph , by defining a vertex-hyperedge cor...

The focus of this article is to develop computationally efficient
mathematical morphology operators on hypergraphs. To this aim we consider
lattice structures on hypergraphs on which we build morphological operators. We
develop a pair of dual adjunctions between the vertex set and the hyper edge
set of a hypergraph H, by defining a vertex-hyperedge...

For a set $S$ of vertices and the vertex $v$ in a connected graph $G$,
$\displaystyle\max_{x \in S}d(x,v)$ is called the $S$-eccentricity of $v$ in
$G$. The set of vertices with minimum $S$-eccentricity is called the $S$-center
of $G$. Any set $A$ of vertices of $G$ such that $A$ is an $S$-center for some
set $S$ of vertices of $G$ is called a cent...

Magnetic Resonance images play a crucial role in the diagnosis and management of the diseases of the brain. The MRI can acquire cross sectional images of our body, based on T1 and T2 relaxation of the tissues. As the information presented in these two images is often complimentary, both these images need to be compared for accurate clinical diagnos...

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coeffici...

An intelligent classification technique for MR brain images are extremely important for medical analysis and treatment selection. Manual interpretation of these images by physicians may lead to wrong diagnosis when a large number of MRIs are analyzed. In this paper an automated decision support system for classification is proposed. It consists of...

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches...

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse featur...

The median problem is a classical problem in Location Theory: one searches for a location that minimizes the average distance to the sites of the clients. This is for desired facilities as a distribution center for a set of warehouses. More recently, for obnoxious facilities, the antimedian was studied. Here one maximizes the average distance to th...

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, inpu...

Learning Disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent meth...

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image conten...

Given a non empty set S of vertices of a graph, the partiality of a vertex with respect to S
is the difference between maximum and minimum of the distances of the vertex to the vertices
of S. The vertices with minimum partiality constitute the fair center of the set. Any vertex set
which is the fair center of some set of vertices is called a fair s...

In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvat...

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an...

Multispectral approach to brain MRI analysis has shown great advance recently in pathology and tissue analysis. However, poor performance of the feature extraction and classification techniques involved in it discourages radiologists to use it in clinical applications. Transform based feature extraction methods like Independent Component Analysis (...

Multispectral analysis is a potential approach in simultaneous analysis of brain MRI sequences. However, conventional classification methods often fail to yield consistent accuracy in tissue classification and abnormality extraction. Feature extraction methods like Independent Component Analysis (ICA) have been effectively used in recent studies to...

Magnetic resonance images play a vital role in identifying various brain related problems. Some of the diseases of the brain show abnormalities predominately at a particular anatomical location which on MR appears at a slice at defined level. This paper proposes a novel technique to locate desired slice using Rotational, Scaling and Translational (...

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to va...

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is ba...

Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper,...

A profile is a finite sequence of vertices of a graph. The set of all vertices of the graph which minimises the sum of the distances to the vertices of the profile is the median of the profile. Any subset of the vertex set such that it is the median of some profile is called a median set. The number of median sets of a graph is defined to be the me...

Almost self-centered graphs were recently introduced as the graphs with exactly two non-central vertices. In this paper we characterize almost self-centered graphs among median graphs and among chordal graphs. In the first case P 4 and the graphs obtained from hypercubes by attaching to them a single leaf are the only such graphs. Among chordal gra...

An antimedian of a profile $\\pi = (x_1, x_2, \\ldots , x_k)$ of vertices of a graph $G$ is a vertex maximizing the sum of the distances to the elements of the profile. The antimedian function is defined on the set of all profiles on $G$ and has as output the set of antimedians of a profile. It is a typical location function for finding a location...

Gray Level Co-occurrence Matrices (GLCM) are one of the earliest techniques
used for image texture analysis. In this paper we defined a new feature called
trace extracted from the GLCM and its implications in texture analysis are
discussed in the context of Content Based Image Retrieval (CBIR). The
theoretical extension of GLCM to n-dimensional gra...

We describe in the present work all minimal clique separators of the four standard products–Cartesian, strong, direct, and lexicographic–as well as all maximal atoms of the Cartesian, strong and lexicographic product, while we only partially describe maximal atoms of direct products. Typically, a product has no clique separator and so the product i...

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one
or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a
cause of c...

Handwritten character recognition is always a frontier area of research in
the field of pattern recognition and image processing and there is a large
demand for OCR on hand written documents. Even though, sufficient studies have
performed in foreign scripts like Chinese, Japanese and Arabic characters, only
a very few work can be traced for handwri...

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Ind...

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters...

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction....

help doctors to treat people with heart problems. In the event of heart attack due to severe artery block, affected portion of the heart muscles might become dead resulting in a scar. Using contrast (a type of dye) injection these dead parts will be seen as bright segments in the MRI scan. The analysis of these images is mostly qualitative at the m...

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug - like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 co...

Content Based Image Retrieval systems open new research areas in Computer Vision due to the high demand of image searching methods. CBIR is the process of finding relevant image from large collection of images using visual queries. The proposed system uses multiple image queries for finding desired images from database. The different queries are co...

The objective of this study is the classification of mammogram images into benign and malignant using Artificial Neural Network.
This framework is based on combining Local Binary Patterns, Haar Wavelet features and Haralick Texture features. The study
shows the importance of Computer Aided Medical Diagnosis in successful decision making by calculat...

This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attribute...

This paper presents an optimum speaker independent isolated digit recognizer for Malayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization. The powerful and well accepted pattern recognition technique Hidden Markov Model is used for acoustic modeling. The training data base has the ut...

This paper highlights the two machine learning approaches, viz. Rough Sets and Decision Trees (DT), for the prediction of Learning Disabilities (LD) in school-age children, with an emphasis on applications of data mining. Learning disability prediction is a very complicated task. By using these two approaches, we can easily and accurately predict L...

The aim of this study is to show the importance of two classification techniques, viz. decision tree and
clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of
all children enrolled in schools. The problems of children with specific learning disabilities have been a
cause of concern to parents...

Voice is the natural communication system used by all beings, human beings in particular. Understanding and recognizing human uttered voice for various applications is the core technology of "information" age. Automatic speech recognition has wide spread applications in real life situations. Here speech recognition of Malayalam isolated digit is cr...

The distance DG(v) of a vertex v in an undirected graph G is the sum of the distances between v and all other vertices of G. The set of vertices in G with maximum (minimum) distance is the antimedian (median) set of a graph G. It is proved that for arbitrary graphs G and J and a positive integer r > 2, there exists a connected graph H, such that G...