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              <text>Implementation of Morphological Gradient Algorithm for Edge Detection</text>
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              <text>Colab; CPU; Dilation; Erosion; MATLAB; Morphological gradient</text>
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              <text>This paper shows the implementation of a morphological gradient in MATLAB and colab platforms to analyze the time consumed on different sizes of grayscale images and structuring elements. A morphological gradient is an edge detecting technique that can be derived from the difference of two morphological operations called dilation and erosion. In order to apply the morphological operations to an image, padding is carried out which involves inserting 0 for dilation operation and 225 for erosion. Padding for the number of rows or columns is based on the size of the structuring element. Further, dilation and erosion are implemented on the image to obtain morphological gradient. Since central processing unit (CPU) implementation follows sequential computing, with the increase in the image size, the time consumption also increases significantly. To analyze the time consumption and to verify the performance across various platforms, the morphological gradient algorithm is implemented in MATLAB and colab. The results demonstrate that colab implementation is ten times faster when constant structuring element with varying image size is used and five times faster when constant image size with varying structuring element size is used than the MATLAB implementation.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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          <name>Creator</name>
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              <text>Vardhan Rao M.A.; Mukherjee D.; Savitha S.</text>
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              <text>Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 773-789.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-16-9416-5_57" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-16-9416-5_57&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISSN: 23674512</text>
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              <text>Online</text>
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              <text>Vardhan Rao M.A., Department of Computer Science and Engineering, School of Engineering, Christ University, Bangalore, India; Mukherjee D., Department of Computer Science and Engineering, School of Engineering, Christ University, Bangalore, India; Savitha S., Department of Computer Science and Engineering, School of Engineering, Christ University, Bangalore, India</text>
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