Abstract
Identifying plant species based on a leaf image is a challenging task. This paper presents a leaf recognition system using orthogonal moments as shape descriptors and Histogram of oriented gradients (HOG) and Gabor features as texture descriptors. Th e shape descriptors captures the global shape of leaf image. The internal vein structure is captured by the texture features. The binarized leaf image is pre-processed to make it scale, rotation and translation-invariant. The Krawtchouk moments are computed from the scale and rotation normalized shape image. The HOG feature is computed on rotation normalized gray image. The combined shape and texture features are classified with a support vector machine classifier (SVM).
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Pradeep Kumar, T., Veera Prasad Reddy, M., Bora, P.K. (2017). Leaf Identification Using Shape and Texture Features. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_48
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DOI: https://doi.org/10.1007/978-981-10-2107-7_48
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