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Robotic data acquisition of sweet pepper images for research and development
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel.ORCID-id: 0000-0003-4685-379x
Department of Computer Science, Ben-Gurion University of the Negev, Beer Sheva, Israel .
Department of Computer Science, Ben-Gurion University of the Negev, Beer Sheva, Israel .
Irmato Industrial Solutions Veghel B.V., Veghel, The Netherlands .
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2016 (Engelska)Konferensbidrag, Muntlig presentation med publicerat abstract (Refereegranskat)
Abstract [en]

A main problem limiting the development of robotic harvesters is robust fruit detection [5]. Despite intensive research conducted in identifying the fruits and their location [2,3], current fruit detection algorithms have a limited detection rate of 0.87 which is unfeasible from an economic perspective [5]. The complexity of the fruit detection task is due to the unstructured and dynamic nature of both the objects and the environment [4-6]: the fruit have inherent high variability in size, shape, texture, and location; occlusion and variable illumination conditions significantly influence the detection performance[3].

A common practice for image processing R&D for complicated problems is the acquisition of a large database (e.g., Labelme open source labeling database [1], Oxford building dataset [2]). These datasets enable to advance vision algorithms development [7] and provide a benchmark for evaluating new algorithms. To the best of our knowledge, to date there is no open dataset available for R&D in image processing of agricultural objects. Evaluation of previously reported algorithms was based on limited data [5]. Previous research indicated the importance of evaluating algorithms for a wide range of sensory, crop, and environmental conditions [5].

A robotic acquisition system and procedure was developed using a 6 degree of freedom manipulator, equipped with 3 different sensors to automatically acquire images from several viewpoints with different sensors and illumination conditions. Measurements were conducted along the day and at night in a commercial greenhouse and resulted in a total of 1764 images from 14 viewpoints for each scene. Additionally, drawbacks and advantages of the proposed approach as compared to other approaches previously utilized will be discussed along with recommendations for future acquisitions.

Ort, förlag, år, upplaga, sidor
2016.
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Forskningsämne
data- och systemvetenskap
Identifikatorer
URN: urn:nbn:se:oru:diva-79444OAI: oai:DiVA.org:oru-79444DiVA, id: diva2:1389081
Konferens
The 5th Israeli Conference on Robotics 2016, Air Force Conference Center Hertzilya, Israel, 13-14 April, 2016
Forskningsfinansiär
EU, Horisont 2020, 66313Tillgänglig från: 2020-01-28 Skapad: 2020-01-28 Senast uppdaterad: 2020-02-24Bibliografiskt granskad

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Robotic Data Acquisition of Sweet Pepper Images for Research and Development(112 kB)27 nedladdningar
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Kurtser, Polina

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Kurtser, PolinaEdan, Yael
Datorseende och robotik (autonoma system)

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