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Conditional based Edge Detection Algorithm Enhancing the Quality of Clustered Grain Seeds

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Authors:
Honeyily, Disha Sugha, Vinay Thakur
10.5120/ijca2019919203

Honeyily, Disha Sugha and Vinay Thakur. Conditional based Edge Detection Algorithm Enhancing the Quality of Clustered Grain Seeds. International Journal of Computer Applications 178(33):12-15, July 2019. BibTeX

@article{10.5120/ijca2019919203,
	author = {Honeyily and Disha Sugha and Vinay Thakur},
	title = {Conditional based Edge Detection Algorithm Enhancing the Quality of Clustered Grain Seeds},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2019},
	volume = {178},
	number = {33},
	month = {Jul},
	year = {2019},
	issn = {0975-8887},
	pages = {12-15},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume178/number33/30750-2019919203},
	doi = {10.5120/ijca2019919203},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this study, we proposed a method of improving the edge detection of clustered grains (soybean seeds) to identify the actual shape of grain seeds and enhance the edge of seeds with the help of a conditional Sobel operator based edge. We designed methods that improve the edges of clustered soybean seeds from a digital image captured under non-ideal conditions. This is not mandatory, but results will be more reliable if that condition is observed. Basically, we compared some parameter that is energy, mean, median and range of image with respective base paper.

References

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Keywords

Edge detection, Clustered seeds, soybean seeds, Digital Image, Image enhancement.