Classification of Rice Leaf Spot Disease using Local Binary Patterns
Sachin Kumar1, Amal Ghosh T A2, Sreekumar K3
1Sachin Kumar*, Dept. of Computer Science & IT, Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India.
2Amal Ghosh T A, Dept. of Computer Science & IT, Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India.
3Sreekumar K, Dept. of Computer Science & IT, Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 27, 2020. | Manuscript published on April 10, 2020. | PP: 510-512 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3866049620/2020©BEIESP | DOI: 10.35940/ijitee.F3866.049620
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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: The fundamental objective of this work is to develop an image processing framework that can perceive a proper methodology for Content Based Image Retrieval (CBIR) in Leaf Inadequacy. The salient point selection concept is utilized by selecting the Salient points from the edgy image and the concept of inter-plane relationship method is imposed, Local Binary Patterns (LBPs) are computed with respect to the center pixel of the salient point. The research work consists primarily of three sections, namely representation of the leaf image, extraction of features and classifying. During the extraction process of the application the most important and special features of the image are retrieved. The image is contrasted with the data base images in the classification phase. The surface of the plant leaf is divided into smaller regions using which the LBP is obtained and the combination of them produces a single feature vector. An accurate model is constructed by this feature vector which is used to measure differences between flawed and healthy plant images.
Keywords: Edgy Salient points Local Binary Patterns (LBPs), Content-Based Image Retrieval (CBIR), Leaf Deficiency (LD).
Scope of the Article: Image Processing and Pattern Recognition