Abstract
In this paper we propose a novel framework for segmentation of mango regions from its tree image. The proposed framework consists of mango localization followed by mapping of boundary information to the located region for segmentation. Initially thresholding is applied to each individual color band R,G and B by adaptive thresholding and later they are combined back. Application of smoothing and binarization to the combined image gives the location of mangoes along with noise. The texture features are extracted from each location then matched with template stored in the database to eliminate the noisy regions. Finally, locations of the mangoes are obtained and edge information is superimposed on to those locations for segmentation. An experiment is performed on our own dataset and efficiency is evaluated by computing the precision, recall and F-measure with respect to the human segmented images considering as a ground truth.
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References
Bramley, R.G.V., Proffit, A.P.B., Hinze, C.J., Pearse, B., Hamilton, R.P.: Generating benefits from precision viticulture through selective harvesting. In: Proceedings of the 5Th European Conference on Precision Agriculture, pp. 891–898 (2005)
Ducournau, S., Feutry, A., Plainchault, P., Revollon, P., Vigouroux, B., Wagner, M.H.: An image acquisition system for automated monitoring of the germination rate of sunflower seeds. Computers and Electronics in Agriculture 44, 189–202 (2004)
Zheng, L., Zhang, J., Wang, Q.: Mean-shift-based color segmentation of images containing green. Vegetation Computers and Electronics in Agriculture 65, 93–98 (2009)
Burgos-Artizzu, X.P., Ribeiro, A., Tellaeche, A., Pajares, G., Fernández-Quintanilla, C.: Analysis of natural images processing for the extraction of agricultural elements. Image and Vision Computing 28, 138–149 (2010)
Thorp, K.R., Dierig, D.A.: Color image segmentation approach to monitor flowering in lesquerella. Industrial Crops and Products 34, 1150–1159 (2011)
Deng, Y., Manjunath, B.S.: Unsupervised Segmentation of Color-Texture Regions in Images and Video. Pattern Analysis and Machine Intelligence 23, 800–810 (2001)
Haralick, R.M., Shanmugam, K., Dinstein, I.: Texture Feature For Image Classification. IEEE Transactions on Systems, Man and Cybernetics SMC-3, 610–621 (1973)
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© 2013 Springer International Publishing Switzerland
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Guru, D.S., Shivamurthy, H.G. (2013). Segmentation of Mango Region from Mango Tree Image. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_21
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DOI: https://doi.org/10.1007/978-3-319-03844-5_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03843-8
Online ISBN: 978-3-319-03844-5
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