Seed Classification using Multi Feature Extraction
Surekha R1, R. Shobarani2, G.Victo Sudha George3
1Surekha R, Research Scholar, Dr. M G R Educational and Research Institute, Chennai, India.
2R. Shobarani, Professor, Dr. M G R Educational and Research Institute, Chennai, India.
3G. Victo Sudha George, Professor, Dr. M G R Educational and Research Institute, Chennai, India.
Manuscript received on 10 June 2019 | Revised Manuscript received on 17 June 2019 | Manuscript Published on 19 June 2019 | PP: 635-639 | Volume-8 Issue-8S June 2019 | Retrieval Number: H11080688S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now a day’s research works on agriculture field have been widely incorporated and showing promising growth. The man free system for food processing unit like classification based on variety, quality and other aspect plays a crucial role in the agricultural research. This paper discuss about the seed classification based on multiple feature extraction and minimum distance classifier. Feature extraction is associated with spatial, color, shape, texture and statistical features of the seed. In this work rice, corn and wheat are used as test samples to demonstrate the effectiveness of the Connected Component Analysis and classification process.
Keywords: Classification, Rice, Wheat, Corn, Feature Extraction, Minimum Distance Classifier.
Scope of the Article: Classification