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Author: search.filters.author.Viswanathan, Sangeetha

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    A survey on pattern recognition using spiking neural networks with temporal encoding and learning
    (International Journal of Research in Advent Technology, 2014-11) Viswanathan, Sangeetha
    This paper, recognize of the patterns using spiking neural networks with temporal encoding and learning. Neural networks place the important role in cognitive and decision making process. Processing the different type of inputs lead to find the discriminate the pattern. Leaky Integrate Fire Neurons are used to recognize the patterns. During the recognition supervised learning method is used to make the decision. Temporal encoding and learning of spiking neural network is used to classify effectively. Different spiking neural networks learning algorithm are used to recognize the patterns and also analyze the performance of the particular algorithm which was used in the pattern recognition
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    Cluster analysis of breast cancer data using Genetic Algorithm and Spiking Neural Networks
    (IEEE, 2015) Viswanathan, Sangeetha
    Breast cancer is taking a large toll in the present scenario. Many computer aided diagnosis are been developed to detect breast cancer. The detected breast cancer is also classified according to their subtypes. In the absence of a class definition, analyzing the cancer types is huge some task. Clustering the breast cancer data is a process that merges the feature selection process and the process of defining the class labels for the data. The proposed work has four stages which include preprocessing, feature selection, feature clustering and cluster validation. This paper uses a Spiking Neural Network that is been trained with an Evolution topology algorithm and Genetic Algorithm is used to select the features from the dataset. The result of the network will cluster that classifies the data into abrupt types. The clusters are then validated using DB index
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    Skeletonisation Approaches for Determining Paths in an Image: A Review
    (Indian Journal of Science and Technology, 2015-12) Viswanathan, Sangeetha
    Skeletonisation is an effective way to provide an intact representation of an object’s shape. This approach has great applications in the fields of motion planning, object representation, tracking, information retrieval, topology representation, sensor distribution and location, facility location, forestry application, building constructions etc. Skeletons naturally provide a pixel to boundary mapping through which the path between points can be found in a terrain map. Many approaches for determining the skeleton of a terrain exist. In this paper, the different methods for Skeletonisation are discussed. Initially the various categorizations of Skeletonisation is discussed which is further followed by application of those algorithms for path determining. Quantitative measures for validating the skeleton are also discussed. Finally, the applications of Skeletonisation in various domains are elaborated
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    Evaluation of Distance Functions for the Comparison of Gradient Orientation Histograms
    (Indian Journal of Science and Technology, 2015) Viswanathan, Sangeetha
    Local features of an image are used in many computer vision applications such as object detection and scene matching. The gradient orientation histogram is used by many local features such as Scale Invariant Feature Transform (SIFT), a widely used image local feature. This paper discusses various distance functions that can be used to measure the similarity between the local features described by the gradient orientation histogram. A distance function, based on the quadratic form is proposed for the SIFT descriptor. The state of the art distance functions - Euclidean, Chi-square, Manhattan and the proposed quadratic form based distance function are calculated between the features extracted from the images. Nearest neighborhood ratio strategy is used to find the corresponding features based on the distance measure. Correct matches are estimated using the ground truth transformation function between the images, present in the form of homograph matrix. It is experimentally found that the proposed distance function has an execution time reduced by 21% compared to the Euclidean distance for a similar accuracy performance. The proposed distance retrieves more number of correct matches compared to the modified Earth Mover distance which is fastest among the evaluated distance functions. The future work will be aimed at improving the time taken for computing the distance matrix between the feature sets and a better strategy for computing the matches.
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    Review of Image Fusion Techniques and Evaluation Metrics for Remote Sensing Applications
    (Indian Journal of Science and Technology, 2015) Viswanathan, Sangeetha
    Low resolution Multispectral images obtained from earth observation satellite interpreted directly have less information whichisnot suitable for remote sensing applications.The advancement of sensors onboardsatellitesprovidespanchromatic imageswhich have more image details and low-resolution MS images lead theway for the researchers to develop algorithms suitable for fusing multi-sensor images which can improve the resolution of the MS images. In this paper review on various pixel based fusion algorithms and evaluation metrics are presented. From the literature review, it is inferred that the Multi resolution techniques will give better accuracy than all other traditional algorithms.
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    Spatial Injection to Low Resolution Images using IIHS Transform
    (Indian Journal of Science and Technology, 2015) Viswanathan, Sangeetha
    Image fusion, the process of combining multi-modal or multi-focus images to form a new informative image than input images. The fused image contains more information than their input images which helps remote sensing applications for image analysis efficiently. Many image fusion algorithms have been developed, but all of them introduced a term called as color distortion. The huge difference between the intensity of input images leads to the color distortion. The Intensity-Hue-Saturation fusion technique gives more access to the user to work on pixel by pixel. This method accessibility delivers the good fusion technique base to reduce the color distortion. We proposed an algorithm which solves the color distortion problem effectively and it can produce an output image as highly informative. The difference in intensity of input images reduced by injecting the intensity of the high resolution image. The proposed work performs better than existing algorithms and it is proved by statistical measures like a correlation coefficient, mean, standard deviation, ERGAS, UIQI and spectral angle mapper
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    Super resolution image reconstruction using frequency spectrum
    (Indian Journal of Science and Technology, 2015-12) Viswanathan, Sangeetha
    Super resolution image reconstruction is defined as generating a high resolution image from a low resolution image or sequence of low resolution images captured from identical scene apparently a video. An algorithm for reconstructing a high resolution image from a low resolution image by altering the frequency components is discussed in this paper. In this method the high frequency components of the zoomed low resolution image is modified so as to increase the resolution of the low resolution image. The evaluation for the experiments is based on the performance measure matrix peak signal to noise ratio. The experimental results shown proves that the algorithm is highly advantageous and computationally fast compared to the other interpolation methods. The algorithm will be helpful in practical applications of medical imaging diagnosis, remote sensing and military applications
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    A Modified Fuzzy A* Based Inference System for Path Planning in an Unknown Environment
    (IEEE, 2018-05) Viswanathan, Sangeetha
    One of the major challenges in a path planner system is finding the shortest path in the least time and cost. In this paper, fuzzy logic based A* algorithm is discussed. A* search is a heuristic method and when it is combined with Fuzzy logic, will yield greater global convergence. The proposed method addresses the path -searching behavior with minimum time and risk. In the fuzzy logic architecture, diagonal front-right distance, turn, goal distance, angle and speed are given as the inputs to the fuzzy inference system. Mamdani systems is used as Inference system for a better simulation the experiment is carried out in MATLAB environment and it is found that Fuzzy A* shows a shorter path in less time than the existing A* method.
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    A Normalized Rank Based A* Algorithm for Region Based Path Planning on an Image
    (Springer, 2019-04) Viswanathan, Sangeetha
    With the development of many autonomous systems, the need for efficient and robust path planners are increasing every day. Inspired by the intelligence of the heuristic, a normalized rank-based A* algorithm has been proposed in this paper to find the optimal path between a start and destination point on a classified image. The input image is classified and a normalized rank value based on the priority of traversal on each class is associated with each point on the image. Using the modified A* algorithm, the final optimal path is obtained. The obtained results are compared with the traditional method and results are found to be far better than existing method.
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    An Intelligent Gain based Ant Colony Optimisation Method for Path Planning of Unmanned Ground Vehicles
    (DRDO, 2019) Viswanathan, Sangeetha
    In many of the military applications, path planning is one of the crucial decision-making strategies in an unmanned autonomous system. Many intelligent approaches to pathfinding and generation have been derived in the past decade. Energy reduction (cost and time) during pathfinding is a herculean task. Optimal path planning not only means the shortest path but also finding one in the minimised cost and time. In this paper, an intelligent gain based ant colony optimisation and gain based green-ant (GG-Ant) have been proposed with an efficient path and least computation time than the recent state-of-the-art intelligent techniques. Simulation has been done under different conditions and results outperform the existing ant colony optimisation (ACO) and green-ant techniques with respect to the computation time and path length