Automatic Seed Classification by Shape and Color Features using Machine Vision Technology
نویسندگان
چکیده
منابع مشابه
Automatic Seed Classification by Shape and Color Features using Machine Vision Technology
: In this paper the proposed system uses content based image retrieval (CBIR) technique for identification of seed e.g. wheat, rice, gram etc. on the basis of their features. CBIR is a technique to identify or recognize the image on the basis of features present in image. Basically features are classified in to four categories 1.color 2.Shape 3. texture 4. size .In this system we are extracting...
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Shatadal, P., Jayas, D.S., Hehn, J.L. and Bulley, N.R. 1995. Seed classification using machine vision. Can. Agric. Eng. 37:163-167. This paper reports the results of applying digital image analysis in conjunction with statistical pattern recognition to measure the size and shape features of various seed types and to classify them into the primary grain, small seed, and large seed categories. Th...
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Several methods to identify plants have been proposed by several researchers. Commonly, the methods did not capture color information, because color was not recognized as an important aspect to the identification. In this research, shape and vein, color, and texture features were incorporated to classify a leaf. In this case, a neural network called Probabilistic Neural network (PNN) was used a...
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Content based image retrieval (CBIR) is the task of searching digital images from a large database based on the extraction of features, such as color, texture and shape of the image. Most of the research in CBIR has been carried out with complete queries which were present in the database. This paper investigates utility of CBIR techniques for retrieval of incomplete and distorted queries. Stud...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications Technology and Research
سال: 2013
ISSN: 2319-8656
DOI: 10.7753/ijcatr0202.1023