Abstract
This paper presents a comparison among the techniques which use the texture features as a basis of detection the diseases among the captured leaf images of the Strawberry Plant. Local Binary Pattern, Complete Local Binary Pattern and Local Ternary Patterns are used to extract the features and a comparison of accuracy is shown among them. LBP is used because its features remain unchanged even if the monotonic gray-scale changes like, the effects that are caused due to illumination variations, are present in the image, Complete Local Binary Pattern is used since it conveys more discriminant information of local structure which is ignored by LBP & Local Ternary Patterns are used since it is more robust to noise than LBP which may improve the accuracy of the system. The set of images are taken from Plant Village Dataset. The image dataset contains the healthy leaf images and the Leaf Scorch Diseased Leaf Images.
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Kirti, Rajpal, N., Arora, M. (2021). Comparison of Texture Based Feature Extraction Techniques for Detecting Leaf Scorch in Strawberry Plant (Fragaria × Ananassa). In: Kumar, A., Mozar, S. (eds) ICCCE 2020. Lecture Notes in Electrical Engineering, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-15-7961-5_63
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