Conference Papers
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Item Experimental investigation of the effectiveness of the LC filter in PV fed induction motor water pumping systems with different type of inductors(Institute of Electrical and Electronics Engineers Inc., 2018) Mudlapur, A.; Subrahmanya Adiga, P.; Anusha, R.; Balasubramanian, B.This paper presents the experimental study of the effectiveness of the LC filter in PV fed water pumping systems. This study is very important in water pumping applications where prolonged running conditions is a major concern. LC filters are connected at the terminals of the inverter to avoid transient over voltages across the induction machine. The conventional LC filter with lumped gap inductor is studied initially. The temperature of the filter inductor is monitored to study its behaviour. It is inferred that the inductor temperature increases drastically due to the high winding losses and therefore may lead to system failure when run for longer duration. The inductor is replaced with uniformly distributed(powdered) core and low cost discretely distributed gap core so as to minimize the losses. Comparative study between the conventional and proposed inductors is carried out. It is inferred that discretely distributed gap inductors are a better choice over powdered core inductors. The experimentation is carried out on a 3-HP induction motor and results with lumped gap and discretely distributed gap inductors are presented along with their thermal profiles. Results show that, the discrete distributed gap inductor is the cost effective solution for the LC filter failures in water pumping applications. © 2018 IEEE.Item Frontal Gait Recognition based on Hierarchical Centroid Shape Descriptor and Similarity Measurement(Institute of Electrical and Electronics Engineers Inc., 2019) Anusha, R.; Jaidhar, C.D.Gait recognition is an expanding stream in biometrics, intended to recognize individuals through the investigation of their walking pattern. This pattern is obtained from a distance, without the active participation of the people. One of the difficulties of the appearance-based gait approach is to enhance the performance of frontal gait recognition, as it carries less spatial and temporal data when compared with other view variations. As a result, to increase the performance of the frontal gait recognition, this paper presents a method which uses two-step procedure; the Hierarchical centroid Shape descriptor (HCSD) and the similarity measurement. The proposed method was assessed on the broadly used CASIA A, CASIA B, and CMU MoBo gait databases. The experimental outcomes showed that the proposed method gave promising results and outperforms certain state-of-the-art methods in terms of recognition performance. © 2019 IEEE.Item An Approach to Speed Invariant Gait Analysis for Human Recognition using Mutual Information(Institute of Electrical and Electronics Engineers Inc., 2019) Anusha, R.; Jaidhar, C.D.Gait is a biometric characteristic that facilitates the identification of individuals with low-resolution images. This aspect intensifies its utility in many human detection applications. However, there are many challenges that adversely affect the gait recognition performance. They are caused by the impact of various covariate aspects such as, changes in clothing and carrying conditions, walking speed, walking surface conditions, view variations, and so on. This paper proposes an effective approach for speed-invariant gait recognition system. This approach uses the Region of Interest (ROI) extracted from Gait Energy Image (GEI) to classify a probe sample into a gallery sample. The mutual information obtained from a probe and gallery sample, followed by their classification capture the spatial dynamics of GEI efficiently to improve the gait recognition performance. Further, the proposed method is evaluated on CASIA C and OU-ISIR Treadmill A gait databases. Experimental results demonstrate the capability of the proposed approach in comparison with the existing gait recognition methods. © 2019 IEEE.Item On Human Identification Using Running Patterns: A Straightforward Approach(Springer Verlag service@springer.de, 2020) Anusha, R.; Jaidhar, C.D.Gait is a promising biometric for which various methods have been developed to recognize individuals by the pattern of their walking. Nevertheless, the possibility of identifying individuals by using their running video remains largely unexplored. This paper proposes a new and simple method that extends the feature based approach to recognize people by the way they run. In this work, 12 features were extracted from each image of a gait cycle. These are statistical, texture based and area based features. The Relief feature selection method is employed to select the most relevant features. These selected features are classified using k-NN (k-Nearest Neighbor) classifier. The experiments are carried out on KTH and Weizmann database. The obtained experimental results demonstrate the efficiency of the proposed method. © 2020, Springer Nature Switzerland AG.Item Gaussian Filtered Gait Energy Template and Centroid Corner Distance Features for Human Gait Recognition(Institute of Electrical and Electronics Engineers Inc., 2019) Anusha, R.; Jaidhar, C.D.One of the convincing and latest biometric systems is gait recognition because of its ability to unobtrusively identify an individual at a distance and with low-resolution images. This study proposes an efficient method to enhance the performance of the gait detection system. The gait silhouette images are initially processed with two gait portrayal methods as the feature resources: Gait Energy Image (GEI) and Gaussian Filtered-Gait Energy Image (GF-GEI). Further, an effort has been made to present a statistical shape examination method, which is established on GF-GEI, and it is divided into six independent horizontal segments. The centroid corner distance features obtained from these horizontal segments forms the feature vector of the image. The proposed method is assessed on the widely used CASIA A, CASIA B, and OU-ISIR D gait datasets. The empirical results illustrate that the performance of the proposed approach is promising and surpasses some state-of-the-art gait identification methods recorded in literature. © 2019 IEEE.Item Spatial Dynamics for Identification of Individuals through Gait and Other Locomotion Activities(Institute of Electrical and Electronics Engineers Inc., 2024) Anusha, R.; Sanshi, S.Gait, the pattern of walking, has been extensively studied and various methods have been developed to use it as a biometric for individual recognition. Despite this, the potential to identify individuals through running videos has not been thoroughly explored. The paper introduces a novel method that expands the feature-based approach for identifying individuals based on their running style. This work focuses on extracting the mutual information and location specific metric from the key gait poses of subjects in the testing and training datasets. Later on, the assignment of a testing sample to the training sample is accomplished using the proposed classification method. The experiments are conducted on KTH, OU-ISIR A, and Weizmann database. The efficiency of this method is demonstrated by the obtained experimental results. © 2024 IEEE.Item A Critical Review of MPPT Algorithms for PV Systems(Institute of Electrical and Electronics Engineers Inc., 2024) P, P.; Anusha, R.; Kumar, V.V.; Balasubramanian, B.With the growing population, one of the main issues is electricity. Electrical power can be generated from a variety of conventional or non-renewable and non-conventional or renewable energy resources. However, there are negative effects of using non-renewable energy resources on both the environment and the human population. Searching for an alternate energy source is necessary due to the limited availability of these fossil fuels. Among the alternatives that can be used to generate electricity are renewable energy resources that transform energy from the sun, wind, falling water, etc. Solar energy is one among these energy resources that is available in abundant. The fundamental components of photovoltaic (PV) systems are solar cells, which are connected in parallel and series to produce the necessary amount of power. There is only one peak in the PV panel characteristics when all the panels receive the same amount of insolation. However, PV systems commonly experience non-uniform insolation due to shadowing. Their power-voltage (P-V) curve show several peaks under these circumstances, with a single global maximum power point (GMPP) among all. Operating these panels at GMPP during partial shading conditions (PSC) is a challenging task as the insolation keeps changing frequently. This study gives a detailed review of various maximum power point tracking (MPPT) methods that is used during uniform and PSC. This review will help the researchers to explore the possibility of choosing best alternative MPPT techniques to be incorporated for commercial purpose. © 2024 IEEE.Item Speed-Invariant Gait Recognition Using Correlation Factor Lists for Classroom Attendance Systems(Springer Science and Business Media Deutschland GmbH, 2024) Anusha, R.; Jaidhar, C.D.The way a person walks is an important biometric used in many human detection applications, including classroom attendance systems. In such applications, speed is one of the key factors that can affect the performance of a gait detection system, as the student will enter the classroom at different speeds, depending on various factors. This study proposes an effective approach to reduce the impact of speed variations in a gait detection system. Initially, the proposed approach identifies similar regions between training and test samples. Later, the correlation factor lists are calculated using three proposed features: intensity measure, contour measure, and spatial measure. By capturing minute variations in static data, this method efficiently enhances the performance of a gait detection system. The evaluation of this approach uses CASIA C and OU-ISIR A datasets of gait. The experimental results suggest that this approach shows potential in comparison to other gait recognition methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Item FASE Module Enabled Recognition of Individuals Using Distinct Gait Patterns(Institute of Electrical and Electronics Engineers Inc., 2024) Anusha, R.; Jaidhar, C.D.Extensive research has been conducted on gait, the walking pattern, and multiple methods have been created to utilize it as a biometric for identifying individuals. Nevertheless, there has been limited exploration of identifying individuals in running videos. A novel method is introduced in the paper that extends the feature-based approach to recognize individuals by their running patterns. The gait recognition performance is boosted in this work through the introduction of the Feature Analysis and Sample Elimination (FASE) module, which selects significant data samples using cluster formation, analysis, and elimination. Later on, the assignment of a testing sample to the training sample is achieved through the use of the proposed classification method. The experiments utilize the KTH, OU-ISIR A, and Weizmann databases. The obtained experimental results showcase the effectiveness of the proposed method. © 2024 IEEE.Item High Speed Data Compression Using FPGA(Institute of Electrical and Electronics Engineers Inc., 2025) Dileep Kumar, M.J.; de Castro, G.A.; Anusha, R.; P, P.; Srinivas, B.Efficient data compression is critical in modern digital systems to optimize storage and transmission bandwidth, especially in real-time applications. FieldProgrammable Gate Arrays (FPGAs) provide high-speed, hardware-accelerated solutions for data compression, offering parallel processing capabilities and reduced latency. This paper explores FPGA-based implementations of Run-Length Encoding (RLE) and Delta Encoding, two widely used lossless compression techniques. Performance is analyzed in terms of resource utilization, compression efficiency, power consumption, and scalability using the Xilinx Spartan-6 FPGA. Our results demonstrate that Delta Encoding achieves higher clock frequencies and lower power consumption, making it suitable for incremental data applications. In contrast, RLE excels in compressing redundant data sequences but has higher implementation complexity and variable throughput. The comparative study highlights the tradeoffs between these two methods and provides insights into their suitability for FPGA-based data compression in resourceconstrained environments. © 2025 IEEE.