Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties
This research is aimed at evaluating the texture and shape features using the most commonly used neural network architectures for cereal grain classification. An evaluation of the classification accuracy of texture and shape features and neural network was done to classify four Paddy (rice) grains,...
Main Authors: | Archana Chaugule, Suresh N. Mali |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2014-01-01
|
Series: | Journal of Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/617263 |
Similar Items
-
Colonoscopic Polyp Classification Using Local Shape and Texture Features
by: Pradipta Sasmal, et al.
Published: (2021-01-01) -
Using the Multi-scale Image and Semivariogram Textural to Assist the Classification for the Urban Paddy Area
by: Wu Cheng-Ting, et al. -
Statistical Geometric Features for Texture Classification
by: Chen, Y.Q, et al.
Published: (1995) -
Combining multiple features in texture classification
by: Ng, Liang Shing
Published: (1999) -
Efficient and Automated Herbs Classification Approach Based on Shape and Texture Features using Deep Learning
by: Amgad Muneer, et al.
Published: (2020-01-01)