Computer vision-based dimension measurement system for olive identification


  • Abdullah BEYAZ Ankara University, Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, 06130, Aydınlıkevler, Ankara (TR)



morphological analysis; olive fruit; olive stone; olive leaf; Picual; video processing


Olive tree is an important portion of the human history of Mediterranean nations. On the other hand, local varieties are important for each producer regions and even countries. So, olive cultivars are important for agricultural production for these people. The traditional pomological identifiers of the olive trees based on fruits and leaves, also morphometric analysis of size, additionally shape elliptic analysis of endocarp. Because of this reason, in this study, for the ‘Picual’ olive cultivar identification, a fast and easy method was presented. For this aim, ‘Picual’ olive leaf, fruit, and stone dimension measurement values obtained from real-time video images. ‘Picual’ olive fruit, stone, leaf samples evaluated by using real-time computer vision measurements. Regression analysis was applied to the data which was obtained from real-time video and caliper measurements. According to the regression coefficient results, the regression between caliper length measurement (OLLM) and computer vision video length measurement (OLLCV) found as 98.9%, also the regression between caliper width measurement (OLWM) and computer vision video width measurement (OLWCV) found as 97.9% at ‘Picual’ leaves, additionally, the regression between caliper length measurement (OFLM) and computer vision video length measurement (OFLCV) found as 98.5% the regression between caliper width measurement (OFWM) and computer vision video width measurement (OFWCV) found as 98.1 % at ‘Picual’ fruits, at last, the regression between caliper length measurement (OSLM) and computer vision video length measurement (OSLCV) found as 86.2%, the regression between caliper width measurement (OSWM) and computer vision video width measurement (OSWCV) found as 75.3% at ‘Picual’ stones.


Al-Ruqaie I, Al-Khalifah N, Shanavaskhan A (2016). Morphological cladistic analysis of eight popular olive (Olea europaea L.) cultivars grown in Saudi Arabia using numerical taxonomic system for personal computer to detect phyletic relationship and their proximate fruit composition. Saudi Journal of Biological Sciences 23(1):115-121.

Anonymous (2015). Catalog of Turkey olive varieties. Republic of Turkey Ministry of Agriculture and Forestry.

Anonymous (2020). Volume of olive oil produced in Spain between 2011/2012 and 2018/2019 Retrieved 2020 September 19 from

Arnan X, López BC, Martínez-Vilalta J, Estorach M, Poyatos R (2012). The age of monumental olive trees (Olea europaea) in northeastern Spain. Dendrochronologia 30(1):11-14.

Bari A, Martin A, Barranco D, Gonzalez-Andujar JL, Ayad G, Padulosi S (2002). Use of fractals to capture and analyse biodiversity in plant morphology. Emergent Nature. World Scientific Publishing, Singapore, pp 437-438.

Belaj A, Veral MG, Sikaoui H, Moukhli A, Khadari B, Mariotti R, Baldoni L (2016). Olive genetic resources. In: Rugini E, Baldoni L, Muleo R, Sebastiani L (Eds). The olive tree genome. Compendium of plant genomes. Cham: Springer, pp 27-54.

Beyaz A, Özkaya MT, İçen D (2017). Identification of some Spanish olive cultivars using image processing techniques. Scientia Horticulturae 225:286-292.

Beyaz A, Öztürk R (2016). Identification of olive cultivars using image processing techniques Turkish Journal of Agriculture and Forestry 40(5):671-683.

Blazakis KN, Kosma M, Kostelenos G, Baldoni L, Bufacchi M, Kalaitzis P (2017). Description of olive morphological parameters by using open access software. Plant Methods 13(1):111.

Çetin Ö, Mete N, Şahin M, Sefer F, Kaya H, Güloğlu U, … Uluçay N (2016). Pomological characteristics of Memecik x Uslu hybrid (F1) olive genotypes. Olive Science 6 (1):9-14.

Diaz R, Gil L, Serrano C, Blasco M, Moltó E, Blasco J (2004). Comparison of three algorithms in the classification of table olives by means of computer vision. Journal of Food Engineering 61(1):101-107.

Ennouri K, Rayda BEN, Ercisli S, Fathi BEN, Triki MA (2017). Evaluation of variability in Tunisian Olea europaea L. accessions using morphological characters and computational approaches. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 45(1):262-269.

Grillo O, Mattana E, Fenu G, Venora G, Bacchetta G (2013). Geographic isolation affects inter- and intra-specific seed variability in the Astragalus tragacantha complex, as assessed by morpho-colorimetric analysis. Comptes Rendus Biologies 336(2):102-108.

Guzmán E, Baeten V, Fernández Pierna JA, García-Mesa JA (2013). Determination of the olive maturity index of intact fruits using image analysis. Journal of Food Science and Technology 52(3):1462-1470.

Hannachi H, Breton C, Msallem M, Ben El Hadj S, El Gazzah M, Berville A (2008). Differences between native and introduced olive cultivars as revealed by morphology of drupes, oil composition and SSR polymorphisms: A case study in Tunisia. Scientia Horticulturae 116(3):280-290.

Hegazi AA (2012). Performance of 12 Introduced olive cultivars under Egyptian conditions. Research Journal of Agriculture and Biological Sciences 8(2):98-107.

Ismaili H (2014). Pomological characteristics of main indigenous varieties of olive. IPA Cross Border Conference 2014 Albania - Greece, Vlore, September 2014.

Ismaili H, Cimato A, Dibra I (2011). Interaction between environment olive and impact on production. Proceedings ICE2011. 1st International Conference on Ecosystems, Vol 2. June 4-6, 2011, Tirana, Albania.

Lo Bianco M, Ferrer-Gallego P, Grillo O, Laguna E, Venora G, Bacchetta G (2015). Seed image analysis provides evidence of taxonomical differentiation within the Medicago L. sect. Dendrotelis (Fabaceae). Systematics and Biodiversity 13(5):484-495.

Muzzalupo I (2012). Olive Germplasm: Italian Catalogue of Olive Varieties. BoD–Books on Demand.

National Instruments (2018). “NI Vision 2013 for LabVIEW Help”, NI Vision 2013 for LabVIEW Help, 2018. Retrieved 2018 February 19 from

Navero DB (2000) World catalogue of olive varieties. International Olive Oil Council, Madrid.

O’neal ME, Landis DA, Isaacs R (2002). An inexpensive, accurate method for measuring leaf area and defoliation through digital image analysis. Journal of Economic Entomology 95(6):1190-1194.

Ozdemir Y, Ozturk A, Guven E, Nebioglu MA, Tangu NA, Akcay ME, Ercisli S (2016). Fruit and oil characteristics of olive candidate cultivars from Turkey. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 44(1):147-154.

Petruccelli R, Giordano C, Salvatici MC, Capozzoli L, Ciaccheri L, Pazzini M, … Cimato A (2014). Observation of eight ancient olive trees (Olea europaea L.) growing in the Garden of Gethsemane. Comptes Rendus Biologies 337:311-317.

Pinna S, Grillo O, Mattana E, Canadas E, Bacchetta G (2014). Inter and intraspecific morphometric variability in Juniperus L. Endocarps (Cupressaceae). Systematics and Biodiversity 12(2):211-223.

Piras F, Grillo O, Venora G, Lovicu G, Campus M, Bacchetta G (2016) Effectiveness of a computer vision technique in the characterization of wild and farmed olives. Computers and Electronics in Agriculture 122:86-93.

Prashanth P, Saravanan P, Nandagopal V (2015). Vision based object’s dimension identification to sort exact material. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676, p-ISSN: 2320-3331, Volume 10, Issue 1 Ver. III (Jan – Feb. 2015), pp 11-15.

Riquelme MT, Barreiro P, Ruiz-Altisent M, & Valero C (2008). Olive classification according to external damage using image analysis. Journal of Food Engineering, 87(3), 371-379.

Sabliov CM, Boldor D, Keener KM, Farkas BE (2002). Image processing method to determine surface area and volume of axi-symmetric agricultural products. International Journal of Food Properties 5(3):641-653.

Santo A, Mattana E, Grillo O, Bacchetta G (2015). Morpho-colorimetric analysis and seed germination of Brassica insularis Moris (Brassicaeae) populations. Plant Biology 17:335-343.

Smykalova I, Grillo O, Bjelkova M, Pavelek M, Venora G (2013). Phenotypic evaluation of flax endocarps by image analysis. Industrial Crops and Products 47:232-238.

Toplu C, Yildiz E, Bayazit S, Demirkeser TH (2009). Assessment of growth behaviour, yield, and quality parameters of some olive (Olea europaea L.) cultivars in Turkey. New Zealand Journal of Crop and Horticultural Science 37(1):61-70.

Trujillo I, Ojeda MA, Urdiroz NM, Potter D, Barranco D, Rallo L, Diez CM (2014). Identification of the Worldwide Olive Germplasm Bank of Córdoba (Spain) using SSR and morphological markers. Tree Genetics and Genomes, 10(1):141-155.

van Hintum TJL, Brown AHD, Spillane C, Hodgkin T, (2000). Core collections of plant genetic resources. IPGRI Technical bulletin, p 48

Vanloot P, Bertrand D, Pinatel C, Artaud J, Dupuy N (2014). Artificial vision and chemometrics analyses of olive stones for varietal identification of five French cultivars. Computers and Electronics in Agriculture 102:98-105.

Yang W, Guo Z, Huang C, Wang K, Jiang N, Feng H, … Xiong L (2015) Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer. Journal of Experimental Botany 66(18):5605-5620.

Yildirim AN, Yildirim F, Özkan G, Şan B, Polat M, Aşik H, Dilmaçünal T (2017). The determination of pomological and total oil properties of some olive cultivars grown in Isparta, Turkey. Scientific Papers Series B Horticulture, 61:45-49.




How to Cite

BEYAZ, A. . (2020). Computer vision-based dimension measurement system for olive identification. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 48(4), 2328–2342.



Research Articles
DOI: 10.15835/nbha48411966