Open Access Open Access  Restricted Access Subscription or Fee Access

Design and Implementation of an Algorithm for Selecting Mangifera Indica Crop Fruits Using Machine Vision and Artificial Intelligence


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irecos.v10i11.7880

Abstract


The use of technology in terms of improving the production processes of the agro-industry, is increasing significantly. This paper presents the results of the design of an algorithm based on image processing and artificial intelligence for segmenting fruits of Mangifera Indica, with the purpose to establish the shape, the degree of maturity based on color and to estimate the fruit size. This work can be used as a support tool for the agriculturists, for the management of harvest in the crops. Algorithm results allow to determine the condition of the fruit in the harvesting process, helping agriculturist to improve crop productivity.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords


Image Processing; Artificial Intelligence

Full Text:

PDF


References


F. A. Auat Cheein and R. Carelli, “Agricultural robotics: Unmanned robotic service units in agricultural tasks,” IEEE Ind. Electron. Mag., vol. 7, no. 3, pp. 48–58, 2013.
http://dx.doi.org/10.1109/mie.2013.2252957

Y. Pang, M. Lefsky, G. Sun, and J. Ranson, “Impact of footprint diameter and off-nadir pointing on the precision of canopy height estimates from spaceborne lidar,” Remote Sens. Environ., vol. 115, no. 11, pp. 2798–2809, Nov. 2011.
http://dx.doi.org/10.1016/j.rse.2010.08.025

J. Tang, R. Miao, Z. Zhang, D. He, and L. Liu, “Decision support of farmland intelligent image processing based on multi-inference trees,” Comput. Electron. Agric., vol. 117, pp. 49–56, Sep. 2015.
http://dx.doi.org/10.1016/j.compag.2015.07.012

Z. Husin, A. Y. M. Shakaff, A. H. A. Aziz, R. S. M. Farook, M. N. Jaafar, U. Hashim, and A. Harun, “Embedded portable device for herb leaves recognition using image processing techniques and neural network algorithm,” Comput. Electron. Agric., vol. 89, pp. 18–29, Nov. 2012.
http://dx.doi.org/10.1016/j.compag.2012.07.009

J. C. Pastrana and T. Rath, “Novel image processing approach for solving the overlapping problem in agriculture,” Biosyst. Eng., vol. 115, no. 1, pp. 106–115, May 2013.
http://dx.doi.org/10.1016/j.biosystemseng.2012.12.006

J. G. A. Barbedo, “Using digital image processing for counting whiteflies on soybean leaves,” J. Asia. Pac. Entomol., vol. 17, no. 4, pp. 685–694, 2014.
http://dx.doi.org/10.1016/j.aspen.2014.06.014

Z. Pek, L. Helyes, and A. Lugasi, “Color Changes and Antioxidant Content of Vine and Postharvest-ripened Tomato Fruits,” HortScience, vol. 45, no. 3, pp. 466–468, Mar. 2010.

M. S. Alam and S. Dacharaju, “Three-Dimensional Color Pattern Recognition Using Fringe-Adjusted Joint Transform Correlation With CIELab Coordinates,” IEEE Trans. Instrum. Meas., vol. 59, no. 8, pp. 2176–2184, Aug. 2010.
http://dx.doi.org/10.1109/tim.2009.2031384

C. Bauckhage and K. Kersting, “Data Mining and Pattern Recognition in Agriculture,” KI - Künstliche Intelligenz, vol. 27, no. 4, pp. 313–324, Aug. 2013.
http://dx.doi.org/10.1007/s13218-013-0273-0

F. Rahmani and M. Mahmoodi-Eshkaftaki, “Almond Dispersion Detector for a New Almond Picker Apparatus using Coupled Image Segmentation and Genetic Algorithm,” Int. J. Comput. Appl., vol. 124, no. 9, pp. 24–30, 2015.
http://dx.doi.org/10.5120/ijca2015905426

E. A. Murillo-Bracamontes, M. E. Martinez-Rosas, M. M. Miranda-Velasco, H. L. Martinez-Reyes, J. R. Martinez-Sandoval, and H. Cervantes-de-Avila, “Implementation of Hough transform for fruit image segmentation,” Procedia Eng., vol. 35, pp. 230–239, 2012.
http://dx.doi.org/10.1016/j.proeng.2012.04.185

Z. Xie, C. Ji, X. Guo, and S. Ren, “An object detection method for quasi-circular fruits based on improved Hough transform,” Trans. Chinese Soc. Agric. Eng., vol. 26, no. 7, pp. 157–162, 2010.

N. Kondo, “Automation on fruit and vegetable grading system and food traceability,” Trends Food Sci. Technol., vol. 21, no. 3, pp. 145–152, Mar. 2010.
http://dx.doi.org/10.1016/j.tifs.2009.09.002

S. R. Dubey and A. S. Jalal, “Detection and Classification of Apple Fruit Diseases Using Complete Local Binary Patterns,” in 2012 Third International Conference on Computer and Communication Technology, 2012, pp. 346–351.
http://dx.doi.org/10.1109/iccct.2012.76

D.-J. Lee, J. K. Archibald, and G. Xiong, “Rapid Color Grading for Fruit Quality Evaluation Using Direct Color Mapping,” IEEE Trans. Autom. Sci. Eng., vol. 8, no. 2, pp. 292–302, Apr. 2011.
http://dx.doi.org/10.1109/tase.2010.2087325

A. Rocha, D. C. Hauagge, J. Wainer, and S. Goldenstein, “Automatic fruit and vegetable classification from images,” Comput. Electron. Agric., vol. 70, no. 1, pp. 96–104, Jan. 2010.
http://dx.doi.org/10.1016/j.compag.2009.09.002

X. Wang, W. Huang, C. Jin, M. Hu, and F. Ren, “Fruit recognition based on multi-feature and multi-decision,” in 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, 2014, pp. 113–117.
http://dx.doi.org/10.1109/ccis.2014.7175713

P. Montero-Prado, K. Bentayeb, and C. Nerín, “Pattern recognition of peach cultivars (Prunus persica L.) from their volatile components,” Food Chem., vol. 138, no. 1, pp. 724–731, May 2013.
http://dx.doi.org/10.1016/j.foodchem.2012.10.145

Sridevy, S., Vijendran, A., Survey Report on Image Processing in Agriculture, (2015) International Journal on Information Technology (IREIT), 3 (4), pp. 108-116.

Udaya Kumar, N., Krishna Rao, E.V., Madhavi Latha, M., Multi directional wavelet filter based region of interest compression for low resolution images, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (2), pp. 54-62.
http://dx.doi.org/10.15866/irecap.v5i2.4554

Bazi, S., Nait Said, M.S., Extreme learning machines and particle swarm optimization for induction motor faults detection and classification, (2015) International Review of Electrical Engineering (IREE), 10 (4), pp. 501-509.
http://dx.doi.org/10.15866/iree.v10i4.7048

El Farissi, O., Moudden, A., Benkachcha, S., Benhra, J., Recognition improvement of control chart pattern using artificial neural networks, (2015) International Review on Modelling and Simulations (IREMOS), 8 (2), pp. 227-231.
http://dx.doi.org/10.15866/iremos.v8i2.1946

Sabarinathan, C., Muthu, S., Arunkumar, R., Prediction of wear behavior of epoxy-MWCNTS nanocomposites using artificial neural networks, (2013) International Review on Modelling and Simulations (IREMOS), 6 (5), pp. 1665-1671.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize