Reghunadhan Rajesh

Central University of Kerala · Department of Computer Science

Skin cancer (melanoma) prediction is a necessity for the society. But the early prediction of skin cancer is possible from its dermoscopic images, it often fails due to the visual similarity between different types of melanocytes and the visual similarity with the normal skin. So the development of an automatic system for melanoma recognition can h...

The rapid spread of the novel corona virus disease (COVID-19) has disrupted the traditional clinical services all over the world. Hospitals and healthcare centers have taken extreme care to minimize the risk of exposure to the virus by restricting the visitors and relatives of the patients. The dramatic changes happened in the healthcare norms have...

This paper proposes a novel lightweight shifting sample difference method for efficient epileptic seizure detection from electroencephalogram signals. Unlike most recent seizure detection methods that use complex signal transformations, the shifting sample difference method is based on time-domain and does not require any transformation. The epilep...

Interictal Epileptiform Discharges (IEDs) in routine EEG is crucial evidence of epilepsy in one patient. Though some studies have reported on automated detection of IEDs, the availability of open benchmark datasets for evaluating these methods is limited. This article presents a scalp EEG dataset of pediatric epilepsy patients. The dataset contains...

One of the major challenges that deaf people face in modern societal life is communication. For those engaged in agricultural jobs, efficiency at work and productivity are deeply related to the quality of deciphering the sign language used by the deaf farmers. Employing sign language interpreters is not a pragmatic solution to this problem. There c...

Electroencephalogram signals are the classical gold standard for the diagnosis of seizures. Important information that enables the effective detection of seizure is hidden due to the complex and chaotic nature of electroencephalogram signals. The capability of fractal dimension to extract complex information from signals or images is well utilized...

Empirical mode decomposition (EMD) is a remarkable method for the analysis of nonlinear and non-stationary data. EMD will breakdown the given signal into intrinsic mode functions (IMFs), which can represent natural signals effectively. In this work, the competence of EMD with traditional features to classify the seizure and non-seizure EEG signals...

Empirical mode decomposition (EMD) is a remarkable method for the analysis of nonlinear and non-stationary data. EMD will breakdown the given signal into intrinsic mode functions (IMFs), which can represent natural signals effectively. In this work, the competence of EMD with traditional features to classify the seizure and non-seizure EEG signals...

Automatic sign language recognition provides better services to the deaf as it avoids the existing communication gap between them and the rest of the society. Hand gestures, the primary mode of sign language communication, plays a key role in improving sign language recognition. This article presents a video dataset of the hand gestures of Indian s...

Extraction of blood vessel from the retina is a major task for detecting/diagnosing eye related diseases such as diabetes, glaucoma etc. Manual segmentation is a difficult task and can be made easier by developing automated segmentation algorithms. This paper presents a quick survey of retinal segmentation methods. An entropy based optimal threshol...

The communication barrier and the hearing majority are the key social concerns of the deaf-dumb community that prevent them from accessing the basic and essential services of the life. Eventhough the problem has been addressed with the innovations in automatic sign language recognition, an adequate solution has not yet been attained due to a number...

Automatic detection of epilepsy has become a crucial tool for the treatment of medical-refractory epilepsy and it has gained a great attention of researchers during recent years. Two major bottlenecks in the development of automated epilepsy detection systems are dearth of precise data and deficiency of general algorithms which detects epilepsy wit...

Binary particle swarm optimization (BPSO) algorithm is a nature inspired algorithm which has seen many applications in optimization across disciplines. BPSO algorithm consists of mainly equations for velocity updation and position updation. In this paper some of the modifications for binary particle swarm optimization (PSO) on those equations are s...

Evolutionary algorithm (EA) is considered as a simple, powerful and derivative free optimization technique derived from the concepts of nature with capabilities of parallel implementation. Many researchers have made use of variable length chromosome (VLC) and its related operators in Evolutionary optimization. It can be seen that many organisms sur...

In automatic speech recognition (ASR) visual speech information plays a pivotal role especially in the presence of acoustic noise. This paper provides a short review of the different methods for visual speech recognition systems (VSR). Here, we discuss the different stages of VSR including the face and lip localization techniques and different visu...

These days, image processing techniques are most common in diverse medical applications for the early diagnosis and treatment, predominantly in cancer tumors. Identification of such tumors at the budding stage is a tedious task. Most of the existing methods tests on CT (Computed Tomography) scan images that is having mainly four stages: image enhan...

Pedestrian detection is one of the important computer vision problems in automotive safety and driver assistance domain. It is a major component of the advanced driver assistance system (ADAS) which help the driver to drive safely. Recent literature shows a number of research activities addressing object detection/tracking in general and pedestrian...

Automatic classification and prediction of epileptic electroencephalogram (EEG) signal are of great concern to the research community due to its non-stationary and non-linear properties. Features with minimal computation cost are highly needed for the rapid real-time precise diagnosis and implementation in the EEG scanning devices. Even though ener...

Epilepsy is a common neurological disorder and the number of epilepsy patients around the world is increasing in an alarming rate. Identifying and controlling epilepsy is a challenging task. Traditionally, electroencephalogram (EEG) is the most dependable method for the rigorous understanding of epilepsy states. In this paper, a fusion of signal an...

Particle swarm optimization and fuzzy logic have shown their fruits for many years across the fields of science. Fuzzy logic acts as an intelligent layer to any conventional system. Recently fuzzy logic has been used to improve the performance of particle swarm optimization (PSO). This paper presents a novel fuzzy rule based binary PSO (FRBPSO) for...

Software testing is one of the important and crucial phases of software development life cycle. In context of time, cost and effective testing the prime need is test case optimization. In present testing scenario the meta-heuristic methods are used for optimization problem and also provide good optimized result. The most popular algorithm used meta...

High Dimensional data spaces are very common in areas like medicine, biology, bioinformatics, web data, text documents. This high dimensionality brings different challenges when applied with algorithms such as slowness, sensitivity to initial values, either early or slow convergence etc. Various algorithm for the large data set has been proposed in...

This paper throws a light on the available clustering techniques and algorithms, k-means is used to cluster standard and satellite image in RGB and HSV color space. Normally satellite images comes with data and noises, in order to extract meaningful information efficiently there is a need of image clustering and performance of clustering based on p...

Facial Expression is the easy way of telling/showing inner feelings. The Facial Expression Recognition system has many applications including human behavior understanding, detection of mental disorders, synthetic human expressions and many more. This paper presents a quick survey of facial expression recognition as well as a comparative study of va...

Regression testing is unavoidable maintenance activity that is performed several times in software development life cycle. Optimization of regression test case is required to minimize the test case (which will in-turn reduce the time and cost of testing) and to find the fault in early testing activity. The two widely used regression test case optim...

High dimensionality is the problem for many research areas. There are huge number of dimensionality reduction methods are available. Broadly they are grouped into two categories feature selection and feature extraction. Feature selection methods select a subset of features based on some criteria while feature extraction methods transform the data i...

The early information from requirement and design phase is very effective in software testing phase and it is also admitted by software requirement engineers (SRE) and software designer’s community. However still most of the regression testing techniques work is performed by taking conventional information from software code. It will be more benefi...

Automatic facial expression recognition system has many applications including, but not limited to, human behavior understanding, detection of mental disorders, and synthetic human expressions. Two popular methods utilized mostly in the literature for the automatic FER systems are based on geometry and appearance. Even though there is lots of resea...

Ultrasound images are used most popularly in medical image processing. The real time, low cost, non-invasive, no radiation features of ultrasound images make it useful for medical image processing applications. An ultrasound image provides the structural information of each organs of human body. Various techniques have been used for image acquisiti...

Forecasting rainfall and thunderstorm is one of the important requirements for planning and management of many applications, including, agriculture, flood and traffic. Considering the relevance and importance of the study, this research study aims at classification of rainfall and thunderstorm. There are various classifiers available but not limite...

With the advancement of technology huge amount of high dimensional data are getting generated. This paper present's the high dimensional data as a serious problem for computational analysis. Broadly high dimensional data could be handled in two ways, firstly with dimensionality reduction, secondly without dimensionality reduction using classical ma...

Pedestrian detection is one of the major applications addressed in Advanced Driver Assistance Systems (ADAS). There are two approached in detecting pedestrians from a 2D image. One approach is called template matching, where a set of pedestrian templates are matched with various parts of the image in different scales whereas the other method involv...

Pedestrian Protection is of superior importance in automotive safety because almost two third of the deaths in road accidents are involving pedestrians. Advanced Driver Assistance Systems (ADAS), used to guide drivers to drive their vehicles safely, takes care of this issue and identified pedestrian detection and protection as one of its primary fo...

Chemoinformatics, the brain child of Frank Brown [1], has now evolved into a new branch of science, which has high correlations with computer science, bioinformatics, and chemistry. The major functionalities of Chemoinformatics include, but not limited to, chemical structure/property prediction, molecular similarity/diversity analysis, virtual scre...

Chemoinformatics, the brain child of Frank Brown [1], has emerged as new branch of science by the technological marriage of information technology and chemistry [2,3]. Quantitative Structure-Activity Relationships (QSARs), needed for the analysis/drug-design, are in the form of structural alerts that incorporate molecular substructures, presence/ab...

As a lot of information about our body and health can be obtained from a few drops of blood, Kirlian images which are recorded on photographic emulsion using GDV instruments developed in 1996 by Prof. Konstantin Korotkov from St. Petersburg Tech University has the potential to show all the health related issues of our body. This paper deals with th...

As a lot of information about our body and health can be obtained from a few drops of blood, Kirlian images which are recorded on photographic emulsion using GDV instruments developed in 1996 by Prof. Konstantin Korotkov from St. Petersburg Tech University has the potential to show all the health related issues of our body. This paper deals with th...

Fuzzy logic and fuzzy systems are gaining widespread acceptance in a large variety of fields, including but not limited to engineering, commercial, forecasting, artificial intelligence, etc. This paper is for beginners who try to use fuzzy logic in Chemoinformatics. Since, there are lot of uncertainties, vagueness and ambiguity during drug design a...

Image compression techniques help in efficient storage and transmission of images. In this paper we propose a lossy compression technique for two dimensional images. The proposed technique uses bandlet transform to capture the anisotropic regularity of edge structures apart from capturing regularity information from smooth regions. Then type II fuz...

Classification of particular group of agricultural images into semantically meaningful categories is a challenging task. Recently color coherence vector has become popular for image mining. This study makes use of multicolor coherence feature with multiple guide images (MGMCF) for classification of agricultural images like coconut and palm trees. T...

Coconut palms are affected by a number of diseases, some of which are dangerous and the disease gradually reduces the strength of the palm causing severe loss in the yield. This paper deals with the classification of coconut tree leaves which are affected by one of the diseases named as 'leaf rot'. A new feature helpful for the classification of le...

Chemoinformatics has evolved by the marriage of two branches of sciences namely, chemistry and information technology. In this paper, neural network trained by evolutionary algorithm is used as a classifier for the classification of Chemoinformatics data sets. The results of evolutionary neural network classifier are promising.

Gender (Male/Female) classification plays a primary vital role to develop a robust Automatic Tamil Speech Recognition (ASR) applications due to the diversity in the vocal tract of speakers. Various features including Formants (F1, F2, F3, F4), Zero Crossings, and Mel-Frequency Cepstral Coefficients (MFCCs) etc. have appeared in the literature espec...

Aura is the electromagnetic field that surrounds the human body and every organisms and objects in the universe. Illness may be represented by characteristic defects in the finger based aura images which correspond to the main organs of the body. The main focus of this paper is to exemplify the role of aura image in medical diagnosis. Experiments h...

Medical Imaging is an application of image processing in which normalization is one of the important process involved in most of the medical image analysis. Normalization is the process of mapping source image with same stereotaxic space. This can be done by registering each image to the same template, where template can be constructed by consideri...

Ant Colony Optimization (ACO) is used to detect edges in digital images. Such techniques generate a pheromone matrix that represents the edge information at each pixel position on the routes formed by ants dispatched on the image. In this paper a modified ACO-based edge detection is proposed. Ants try to find possible edges by using a heuristic inf...

Classification of words plays a primary vital role to develop a robust automatic speech recognition (ASR) applications due to the diversity in the vocal tract of speakers. This paper presents Neural Network based word classification using the combination of features like, MFCC, Zero Crossing, Zero-Crossing Rate (ZCR) and Formants. The results of wo...

This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Ex- periments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The re- sults based on the combination of other features gave better recogn...

The result of image thresholding is not always satisfactory due to the disturbing factors like vagueness, non- uniform illumination etc and to overcome these problems recently various researchers have proposed fuzzy image thresholding. The linear index of fuzziness for type-1 fuzzy sets by Zenzo et. al. and measure of ultrafuzziness for type-2 fuzz...

Pedestrian classification is addressed by T. Watanabe et al. using SVM with 34704 CoHOG features. This paper addresses the pedestrian classification using neural network with 1344 CoHOG features (feature size is 25 times small) and still achieve comparable results.

Among all the techniques developed for personal authentication, fingerprint recognition system is the most visible one due to its wide range of successful applications in many disciplines such as computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services, etc. This paper...

Digital image acquisition and processing techniques plays very important role in current-day medical diagnosis. Images of living objects are taken using different modalities like X-ray, Ultrasound, Computed Tomography (CT), Magnetic Resonance Imaging (MRI) etc. During the acquisition process, there could be distortions in the images, which will neg...

Rough Set theory represents a promising technique to handle imperfect knowledge, which has found interesting extensions and various applications. This paper presents a note on rough set theory that will be useful for beginners.

Chemoinformatics is the application of information technology in design, creation, organization, management, retrieval, analysis, visualization and use of chemical information to solve chemical problems and drug design. This paper presents a quick survey on chemoinformatics, tools and its applications.

Kirlian photography captures the distribution of human bio-energy field called an Aura. Illness may be represented by characteristic defects in the finger images which correspond to the main organs of the body. In this paper, the main focus is to understand the abnormal energy levels in the body which will/may lead to diseases. Experiments have bee...

Image segmentation has long been an important focus of research, yielding many automated methods to perform segmentation of different organs in the human body. Brain image segmentation is an important but inherently difficult problem in medical image processing. In general, it cannot be solved using straightforward, conventional image processing te...

Learning time is an important factor while designing any computational intelligent algorithms for classifications, medication, control etc. Recently, Extreme Learning Machine has been proposed, which significantly reduce the amount of time needed to train a Neural Network. It has been widely used for many applications. This paper surveys ELM and it...

Journal impact factors are not representatives of the quality measures of individual journal articles, authors and quality factor of journals. Hence, due to the high necessity of quality measures, this paper presents new quality measures for journals, authors and individual journal articles.

Medical image segmentation is a complex and challenging task due to the intrinsic nature of the images. The brain has particularly complicated structure and its precise segmentation is very important for detecting tumors, edema, and necrotic tissues, in order to prescribe appropriate therapy. Recently, rough sets and fuzzy sets has proved its sound...

This paper presents the design and development of Simple Type-2 Takagi-Sugeno Fuzzy Control System (ST2TSFCS) for the nonlinear mathematical model of gyros, which are commonly used in inertial guidance systems, autopilot systems, and the like for sensing angular motion. Type-2 SemiCircular membership function is used for fuzzy linguistic values in...

Images have to be compressed in order to store and transmit them efficiently. We propose a hybrid image compression technique which uses bandlet transform and type-2 fuzzy thresholding. Bandlet transform is used to efficiently represent the anisotropic regularity of edge structures in images and fuzzy thresholding retains the important coefficients...

Due to the increase in the usage of digital images in various fields, digital image compression has become a necessity for the efficient storage and transmission of digital images. This paper presents an extensive survey of various image compression techniques.

Even though the application of Type-1 Fuzzy Sets (T1 FS) has been successful in all applications, since its introduction by Zadeh in 1965, it has limited capabilities to directly model and minimize the effect of uncertainties. In late 1975, Zadeh introduced the concept of Type-2 Fuzzy Sets (T2 FS). T2 FS are described by Membership Functions (MFs)...

Rough set is approximate representation of a crisp set. Rough set theory provides an approach to approximation of sets that leads to useful forms of granular computing. Several applications have revealed the need to extend the traditional rough set approach. A special place among various extensions is taken by the approach that replaces the relatio...

Soft computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found wide applications. One of the most important applications is image segmentation. The process of partitioning a digital image into multiple regions or sets of pixels is called...

The usage of XML data in the World Wide Web and elsewhere as a standard for the exchange of data and to represent semi structured data tends to develop the various tools and techniques to perform various data mining operations on XML documents and XML repositories. In recent years, several encouraging methods have been identified and developed for...

Four dimensional medical images, namely fMRI, require a large volume of memory to store the data. Compression techniques are therefore used for the storage and transmission of these medical images. This paper proposes a coding scheme for volumetric images which in the first stage recognizes significant images and in the second stage compresses thos...

Medical image compression techniques should give high compression ratios apart from preserving vital information in medical images. In this paper we propose a compression technique for four-dimensional functional Magnetic Resonance Images (fMRI). The proposed technique uses bandelet transform to capture the anisotropic regularity of edge structures...

Neuro-anatomical configuration of brain shapes can be analyzed by different methods, in which, structural information of brain shapes can be statistically visualized through modalities like, PET, MRI and fMRI. Extracting information from three dimensional time series of brain is still a challenging task of medical researchers and radiologists studi...

This paper presents novel technique for the design of Mamdani type fuzzy controller using Genetic Algorithm with Variable Length Chromosome based Rule Generation scheme (GAVLCRG). This scheme helps for efficient ways of sampling the search space with varying length dimensionalities and there by simultaneously optimizing the number of rules and the...

This paper focuses on finding the image features in both spatial and wavelet domain and applied that for greenery and non-greenery image classification. The spatial color feature called guided color coherence feature(GCCF) & guided distance feature in wavelet(GDFW) are calculated for the purpose of classification. The color coherence vector is cons...

Security of computers and the networks that connect them is increasingly becoming of great significance. Machine learning techniques such as Decision trees have been applied to the field of intrusion detection. Machine learning techniques can learn normal and anomalous patterns from training data and generate classifiers that are used to detect att...