P. Ganesan

Bio: P. Ganesan is an academic researcher from Sathyabama University. The author has contributed to research in topics: Image segmentation & Color space. The author has an hindex of 15, co-authored 60 publications receiving 754 citations. Previous affiliations of P. Ganesan include Centre for Development of Advanced Computing & Council for Higher Education Accreditation.

Segmentation and edge detection of color images using CIELAB color space and edge detectors

Abstract: Image segmentation refers to a process by which a raw input image is partitioned into non-overlapping regions such that each region is homogenous and connected, and the union of no two spatially adjacent regions is homogeneous. The objective of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. This paper reviews the modified segmentation method for color images based on CIELAB Color Space and Edge detection of color images using the various edge detectors. This work aims to identify/segment different colors in an image by analyzing the CIELAB color space which enables to quantify these visual differences. This proposed method has been tested with images of various formats, size and resolution and the results are proven to be better

Repayment behaviour in credit and savings cooperative societies

Abstract: Purpose – Like other developing countries, Rwandan rural credit market is repressed, shallow, segmented, inefficient and dual structured where both formal and informal financial systems operate side by side. While the later has been playing a predominant role, cooperative societies have emerged as an apt method of increasing the delivery of formal rural credit and savings facilities on sustainable and non‐exploitative terms albeit of financial imprudence stemming from poor credit repayment records. Thus, the purpose of this paper is to examine the factors contributing to credit repayment behaviour among the members of savings and credit cooperative societies in rural Rwanda.Design/methodology/approach – Both exploratory and descriptive designs are used for primary data collection on variables contributing to the repayment behaviour in savings and cooperative societies. Thereafter, a binary logistic regression empirical model is employed to estimate the contribution of each variable to credit repayment rat...

Assessment of satellite image segmentation in RGB and HSV color space using image quality measures

Abstract: This paper presents a comparative study of the segmentation of satellite images in RGB and HSV color space using modified fuzzy c means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. These parameters measure the similarity between the input and the segmented image on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The experiments are performed on GeoEye-1 satellite images to test the efficiency and robustness of the proposed method

HSV color space based segmentation of region of interest in satellite images

Abstract: In this paper, a new method for the extraction of the necessary object or region from the satellite image is proposed. This color based method is based on HSV color space and histogram threshold. Usually the multispectral images received from satellite are in RGB color space. But human eye is more sensitive to intensity than color information (hue or saturation). In the proposed approach, the satellite image in RGB color space is transformed into HSV color space and then the transformed satellite image is split into three different components (channels or images) based on intensity and color. This HSV color space is designed to approximate the human vision. In the next step, the histogram for all three components (hue, saturation and value) is computed and plotted. Then the threshold value is separately applied to all three components. Finally the morphological operations like masking, filtering, smoothening is performed for the extraction of the desired region. The effectiveness of the proposed approach has been demonstrated by number of experiments. Experimental result demonstrates that the proposed method is more efficient in the extraction and segmentation of a desired object or region in the satellite images.

Research Methods in Health. Investigating health and health services

Abstract: This new edition of Ann Bowling's well-known and highly respected text has been thoroughly revised and updated to reflect key methodological developments in health research. It is a comprehensive, easy to read, guide to the range of methods used to study and evaluate health and health services. It describes the concepts and methods used by the main disciplines involved in health research, including: demography, epidemiology, health economics, psychology and sociology.The research methods described cover the assessment of health needs, morbidity and mortality trends and rates, costing health services, sampling for survey research, cross-sectional and longitudinal survey design, experimental methods and techniques of group assignment, questionnaire design, interviewing techniques, coding and analysis of quantitative data, methods and analysis of qualitative observational studies, and types of unstructured interviewing. With new material on topics such as cluster randomization, utility analyses, patients' preferences, and perception of risk, the text is aimed at students and researchers of health and health services. It has also been designed for health professionals and policy makers who have responsibility for applying research findings in practice, and who need to know how to judge the value of that research.

Enhancing Electric Power Quality Using UPQC: A Comprehensive Overview

Abstract: This paper presents a comprehensive review on the unified power quality conditioner (UPQC) to enhance the electric power quality at distribution levels. This is intended to present a broad overview on the different possible UPQC system configurations for single-phase (two-wire) and three-phase (three-wire and four-wire) networks, different compensation approaches, and recent developments in the field. It is noticed that several researchers have used different names for the UPQC based on the unique function, task, application, or topology under consideration. Therefore, an acronymic list is developed and presented to highlight the distinguishing feature offered by a particular UPQC. In all 12 acronyms are listed, namely, UPQC-D, UPQC-DG, UPQC-I, UPQC-L, UPQC-MC, UPQC-MD, UPQC-ML, UPQC-P, UPQC-Q, UPQC-R, UPQC-S, and UPQC-VA. More than 150 papers on the topic are rigorously studied and meticulously classified to form these acronyms and are discussed in the paper.

A review of hand gesture and sign language recognition techniques

Abstract: Hand gesture recognition serves as a key for overcoming many difficulties and providing convenience for human life. The ability of machines to understand human activities and their meaning can be utilized in a vast array of applications. One specific field of interest is sign language recognition. This paper provides a thorough review of state-of-the-art techniques used in recent hand gesture and sign language recognition research. The techniques reviewed are suitably categorized into different stages: data acquisition, pre-processing, segmentation, feature extraction and classification, where the various algorithms at each stage are elaborated and their merits compared. Further, we also discuss the challenges and limitations faced by gesture recognition research in general, as well as those exclusive to sign language recognition. Overall, it is hoped that the study may provide readers with a comprehensive introduction into the field of automated gesture and sign language recognition, and further facilitate future research efforts in this area.

Hand Gesture Recognition Based on Computer Vision: A Review of Techniques

Abstract: Hand gestures are a form of nonverbal communication that can be used in several fields such as communication between deaf-mute people, robot control, human–computer interaction (HCI), home automation and medical applications. Research papers based on hand gestures have adopted many different techniques, including those based on instrumented sensor technology and computer vision. In other words, the hand sign can be classified under many headings, such as posture and gesture, as well as dynamic and static, or a hybrid of the two. This paper focuses on a review of the literature on hand gesture techniques and introduces their merits and limitations under different circumstances. In addition, it tabulates the performance of these methods, focusing on computer vision techniques that deal with the similarity and difference points, technique of hand segmentation used, classification algorithms and drawbacks, number and types of gestures, dataset used, detection range (distance) and type of camera used. This paper is a thorough general overview of hand gesture methods with a brief discussion of some possible applications.