Year 2019, Volume 25 , Issue 4, Pages 427 - 439 2019-12-05

A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions

Yousef ABBASPOUR-GİLANDEH [1] , Sajad SABZİ [2] , Juan IGNACİO ARRİBAS [3]


Segmentation is an important part of each machine vision system that has a direct relationship with the final system accuracy and performance. Outdoors segmentation is often complex and difficult due to both changes in sunlight intensity and the different nature of background objects. However, in fruit-tree orchards, an automatic segmentation algorithm with high accuracy and speed is very desirable. For this reason, a multi-stage segmentation algorithm is applied for the segmentation of apple fruits with Red Delicious cultivar in orchard under natural light and background conditions. This algorithm comprises a combination of five segmentation stages, based on: 1- L*u*v* color space, 2- local range texture feature, 3- intensity transformation, 4- morphological operations, and 5- RGB color space. To properly train a segmentation algorithm, several videos were recorded under nine different light intensities in Iran-Kermanshah (longitude: 7.03E; latitude: 4.22N) with natural (real) conditions in terms of both light and background. The order of segmentation stage methods in multi-stage algorithm is very important since has a direct relationship with final segmentation accuracy. The best order of segmentation methods resulted to be: 1- color, 2- texture and 3- intensity transformation methods. Results show that the values of sensitivity, accuracy and specificity, in both classes, were higher than 97.5%, over the test set. We believe that those promising numbers imply that the proposed algorithm has a remarkable performance and could potentially be applied in real-world industrial case.

background, daylight, machine vision, natural condition, texture, color space
  • Aquino A, Diago M.P, Millan B & Tardaguila J (2017). A new methodology for estimating the grapevineberry number per cluster using image analysis. Biosystem Engineering 156: 80-95.
  • Arroyo J, Guijarro M & Pajares G (2016). An instance-based learning approach for thresholding in crop images under different outdoor conditions. Computers and Electronics in Agriculture 127: 669–679.
  • Bai X, Cao Z, Wang Y, Yu Z, Hu Z, Zhang X & Li C (2014). Vegetation segmentation robust to illumination variations based on clustering and morphology modelling. Biosystem Engineering 125: 80-97.
  • Behroozi-Khazaei N & Maleki M.R (2017). A robust algorithm based on color features for grape cluster segmentation. Computers and Electronics in Agriculture 142: 41–49.
  • Camargo A & Smith J.S (2009). An image-processing based algorithm to automatically identify plant disease visual symptoms. Biosystem Engineering 102: 9–21.
  • Dorj U.-O, Lee M & Yun S.-s (2017). An yield estimation in citrus orchards via fruit detection and counting using image processing. Computers and Electronics in Agriculture 140: 103–112.
  • Gonzalez R.C, Woods R.E & Eddins S.L (2004). Digital Image Processing Using MATLAB. Prentice Hall.
  • Hernández-Hernández J.L, García-Mateos G, González-Esquiva J.M, Escarabajal-Henarejos D, Ruiz-Canales A & Molina-Martínez J.M (2016). Optimal color space selection method for plant/soil segmentation in agriculture. Computers and Electronics in Agriculture 122: 124–132.
  • Kataoka T, Kaneko T, Okamoto H & Hata S (2003). Crop growth estimation system using machine vision, IEEE/ASME Int. Conf. Adv. Intell. Mechatronics (AIM 2003), pp. 1079–1083.
  • Li Y, Cao Z, Lu H, Xiao Y, Zhu Y, Cremers A.B (2016). In-field cotton detection via region-based semantic image segmentation. Computers and Electronics in Agriculture 127: 475–486.
  • Liu X, Zhao D, Jia W, Ruan C, Tang S, Shen T (2016). A method of segmenting apples at night based on color and position information. Computers and Electronics in Agriculture 122: 118-123.
  • Montalvo M, Guerrero J.M, Romeo J, Emmi L, Guijarro M, Pajares G (2013). Automatic expert system for weeds/crops identification in images from maize fields. Expert Systems with Applications 40: 75-82.
  • Onyango C.M & Marchant J.A (2003). Segmentation of row crop plants from weeds using colour and morphology. Computer and electronoc in agriculture 39: 141-155.
  • Slaughter, D.C., Giles, D.K., Downey, D., 2008. Autonomous robotic weed control systems: a review. Computer and Electronoc in Agriculture 61, 63–78.
  • Wisaeng K (2013). A Comparison of Decision Tree Algorithms For UCI Repository Classification. International Journal of Engineering Trends and Technology 4: 3393-3397.
  • Zhao C, Lee W.S, He D (2016). Immature green citrus detection based on colour feature and sum of absolute transformed difference (SATD) using colour images in the citrus grove. Computers and Electronics in Agriculture 124: 243-253.
Primary Language en
Subjects Science
Journal Section Makaleler
Authors

Orcid: 0000-0002-9999-7845
Author: Yousef ABBASPOUR-GİLANDEH (Primary Author)
Institution: University of Mohaghegh Ardabili
Country: Iran


Author: Sajad SABZİ
Institution: University of Mohaghegh Ardabili
Country: Iran


Orcid: 0000-0002-7486-6152
Author: Juan IGNACİO ARRİBAS
Institution: University of Valladolid
Country: Spain


Dates

Application Date : June 15, 2018
Acceptance Date : October 7, 2018
Publication Date : December 5, 2019

Bibtex @research article { ankutbd434137, journal = {Journal of Agricultural Sciences}, issn = {}, eissn = {2148-9297}, address = {}, publisher = {Ankara University}, year = {2019}, volume = {25}, pages = {427 - 439}, doi = {10.15832/ankutbd.434137}, title = {A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions}, key = {cite}, author = {Abbaspour-gilandeh, Yousef and Sabzi, Sajad and Ignacio Arribas, Juan} }
APA Abbaspour-gilandeh, Y , Sabzi, S , Ignacio Arribas, J . (2019). A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions . Journal of Agricultural Sciences , 25 (4) , 427-439 . DOI: 10.15832/ankutbd.434137
MLA Abbaspour-gilandeh, Y , Sabzi, S , Ignacio Arribas, J . "A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions" . Journal of Agricultural Sciences 25 (2019 ): 427-439 <https://dergipark.org.tr/en/pub/ankutbd/issue/50426/434137>
Chicago Abbaspour-gilandeh, Y , Sabzi, S , Ignacio Arribas, J . "A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions". Journal of Agricultural Sciences 25 (2019 ): 427-439
RIS TY - JOUR T1 - A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions AU - Yousef Abbaspour-gilandeh , Sajad Sabzi , Juan Ignacio Arribas Y1 - 2019 PY - 2019 N1 - doi: 10.15832/ankutbd.434137 DO - 10.15832/ankutbd.434137 T2 - Journal of Agricultural Sciences JF - Journal JO - JOR SP - 427 EP - 439 VL - 25 IS - 4 SN - -2148-9297 M3 - doi: 10.15832/ankutbd.434137 UR - https://doi.org/10.15832/ankutbd.434137 Y2 - 2018 ER -
EndNote %0 Tarım Bilimleri Dergisi A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions %A Yousef Abbaspour-gilandeh , Sajad Sabzi , Juan Ignacio Arribas %T A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions %D 2019 %J Journal of Agricultural Sciences %P -2148-9297 %V 25 %N 4 %R doi: 10.15832/ankutbd.434137 %U 10.15832/ankutbd.434137
ISNAD Abbaspour-gilandeh, Yousef , Sabzi, Sajad , Ignacio Arribas, Juan . "A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions". Journal of Agricultural Sciences 25 / 4 (December 2019): 427-439 . https://doi.org/10.15832/ankutbd.434137
AMA Abbaspour-gilandeh Y , Sabzi S , Ignacio Arribas J . A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions. J Agr Sci-Tarim Bili. 2019; 25(4): 427-439.
Vancouver Abbaspour-gilandeh Y , Sabzi S , Ignacio Arribas J . A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions. Journal of Agricultural Sciences. 2019; 25(4): 427-439.
IEEE Y. Abbaspour-gilandeh , S. Sabzi and J. Ignacio Arribas , "A Video Image Segmentation System for the Fruit-trees in Multi-stage Outdoors Orchard under Natural Conditions", Journal of Agricultural Sciences, vol. 25, no. 4, pp. 427-439, Dec. 2019, doi:10.15832/ankutbd.434137