LDA Based Tea Leaf Classification on the Basis of Shape, Color and Texture
ANAMIKA SHARMA, PARUL MALHOTRA, , ,
Affiliations CSE, Sri Sai University ,Palampur, H.P, India
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]
Background/Objectives: The presented paper shows a model of leaf segmentation for tea leaf, its seem to be a promising and feasible approach to perform the task of detecting arbitrary shapes in a tea leaf image with a minimum prior. The performance for given image samples was satisfying. Methods/Statistical analysis: Traditional models were very easy to use in but they did not detect boundaries very accurately. On the other hand proposed algorithm was able to detect boundaries well and will be enhanced with image blending to prove the effectiveness of the technique in real applications. Findings: The results have been displayed in the result section with comparison to previous system in terms of area, time and efficiency. Improvements/Applications: In the proposed LDA system accuracy has been improved.
ANAMIKA SHARMA and PARUL MALHOTRA (2017). LDA Based Tea Leaf Classification on the Basis of Shape, Color and Texture. International Journal of Computer Engineering In Research Trends, 4(12), 543-546. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1201.pdf
Keywords : Segmentation, LDA, PDE, SVM, RGB
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