TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
Classifying Indian Medicinal Leaf Species Using LCFN-BRNN Model |
| 영문제목(English Title) |
Classifying Indian Medicinal Leaf Species Using LCFN-BRNN Model |
| 저자(Author) |
Kiruba Raji I
Thyagharajan K.K
Vignesh T
Kalaiarasi G
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| 원문수록처(Citation) |
VOL 15 NO. 10 PP. 3708 ~ 3728 (2021. 10) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (μ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN’s decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%. |
| 키워드(Keyword) |
Chan-Vese segmentation
Leaky Capacitance and Fired Neuron (LCFN)
time sequence
Bayesian Regularization Neural Network (BRNN)
computer vision
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| 파일첨부 |
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