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International Journal of Food Engineering

Editor-in-Chief: Chen, Xiao Dong

12 Issues per year


IMPACT FACTOR 2016: 0.685

CiteScore 2016: 0.73

SCImago Journal Rank (SJR) 2016: 0.293
Source Normalized Impact per Paper (SNIP) 2016: 0.391

Online
ISSN
1556-3758
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Volume 7, Issue 1 (Jan 2011)

Issues

Suitability of Feature Extraction Methods in Recognition and Classification of Grains, Fruits and Flowers

Basavaraj S Anami / Dayanand G Savakar
Published Online: 2011-01-11 | DOI: https://doi.org/10.2202/1556-3758.1776

This paper presents the suitability of feature extraction methods for the identification and classification of certain agriculture and horticulture crops. Primarily, agriculture/horticulture crops are recognized based on their shape, size, color, texture and the like. When crops exhibit different shapes and sizes, it is customary to choose the shape and size as the basic features. Certain crops are easily identified simply by color; for example, with crops like jowar, ground nut, pomegranate and mango, color becomes the discriminating feature. We have considered color as one of the features in this study. Some agriculture/horticulture crops have overlapping colors, such as wheat and ground nut or mango and orange. When we consider the bulk samples of such grains or fruits, the surface patterns vary from crop to crop. In such cases, the texture becomes ideal for recognition. Hence, we have obtained morphological features, like shape and size, color and textural features, of the image samples to recognize, classify and grade the agriculture/horticulture crops.

Keywords: color features; textural features; morphological features; recognition and classification

About the article

Published Online: 2011-01-11


Citation Information: International Journal of Food Engineering, ISSN (Online) 1556-3758, DOI: https://doi.org/10.2202/1556-3758.1776.

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©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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[1]
Linda S. McDonald, Joseph F. Panozzo, Phillip A. Salisbury, Rebecca Ford, and George-John Nychas
PLOS ONE, 2016, Volume 11, Number 5, Page e0155523
[2]
D. G. Savakar and A. Kannur
Pattern Recognition and Image Analysis, 2016, Volume 26, Number 2, Page 442

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