Abstract
Edge detection determines the boundaries of objects in an Image. Edge detection is a vital concept in object recognition and Image analysis. This paper evaluates the existing edge detection methods and proposes a new edge detection algorithm which uses the morphological operations, sobel operator, Gaussian Smoothing and masking. The novelty of the proposed algorithm is extracting continuous edges in the Image and removing spurious edges using m-connectivity. The paper introduces performance parameters for edge detection to determine which method gives good results. A parameter named Human Perception Clarity (HPC) is mathematically modeled and experimentally proves the efficacy of proposed algorithm.
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Authors would like to thank DBT, New Delhi for sanctioning the Project. Currently this work is carried out under DBT Project.
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Prathusha, P., Jyothi, S. (2018). A Novel Edge Detection Algorithm for Fast and Efficient Image Segmentation. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_26
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DOI: https://doi.org/10.1007/978-981-10-3223-3_26
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