A pattern analysis based underwater video segmentation system for target object detection
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A pattern analysis based underwater video segmentation system for target object detection Rajasekar M.1 · Celine Kavida A.2 · Anto Bennet M.3 Received: 16 March 2019 / Revised: 4 March 2020 / Accepted: 9 March 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Detecting and classifying the target objects in the underwater videos is the primary and essential operation in this modern era. The present works proposed the pattern extraction, segmentation and classification techniques for target object detection in underwater images. These techniques were found to be lacking with the following limitations, such as inefficient computation, inaccurate results, and increased cost-efficiency. Thus, this work targets to introduce a new pattern extraction based classification system for processing underwater images. As the first and foremost thing, the input underwater picture is preprocessed for eliminating the noise by applying the Laplacian Bellman filtering technique. After that, the histogram equalization is utilized to enhance the quality of the source picture. Once the image is noise-free, the patterns are extracted from it with the help of the likelihood gradient pattern technique. Subsequently, the label formation and blob extraction processes are performed in an orderly manner to track the target object accurately. In this work, the novelty is seen implemented in both the preprocessing and the feature analysis stages by developing a novel technique. The significant advantages of this work are: yielding the improved image quality, by being the efficient texture pattern extractor, and they also do not require any additional information and adjustments. While under simulation, the fulfilment attained in the proposed techniques and the appropriate literature methodologies are evaluated and validated with the performance measures like accuracy, sensitivity, specificity, average time, precision, F1measure, and the filtering features like entropy, contrast, and the correlation. Keywords Underwater images · Laplacian bell pattern (LBP) · Likelihood gradient pattern (l.G.P.) · Histogram equalization · Texture pattern extraction · Classification
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Rajasekar M. [email protected]
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Department of Information and Communication Engineering, Research scholar, Anna University, Chennai, Tamil Nadu 600025, India
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Department of Physics, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai 600062, India
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Department of Electronics and Communication Engineering, VEL TECH, Chennai 600062, India
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Multidimensional Systems and Signal Processing
1 Introduction Underwater image processing is an essential and demand task in the field of ocean engineering. The earth is an aquatic planet in which 80% is covered by water (Luan et al. 2014; Qiu et al. 2015). Usually, the underwater images can vary from the natural images and due to its scattering effect and absorption, processing an underwater image is a challenging and demanding problem. During the process of underwate
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