Short communication.: Automatic inspection of the pomegranate (Punica granatum L.) arils quality by means of computer vision

被引:8
作者
Blasco, J. [1 ]
Cubero-Garcia, S. [1 ]
Alegre-Sosa, S. [1 ]
Gomez-Sanchis, J. [1 ]
Lopez-Rubira, V. [2 ]
Molto, E. [1 ]
机构
[1] Inst Valenciano Invest Agr, Ctr Agroingn, Valencia 46113, Spain
[2] Frutas Mira Hermanos, Alicante 03292, Spain
关键词
image analysis; machine vision; on-line sorting; quality;
D O I
10.5424/sjar/2008061-301
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
With the aim of ensuring the quality and homogenising the colour of commercial batches of pomegranate arils, a new prototype for the automatic inspection of pomegranate arils and their separation into categories by means of air ejectors has been developed. Arils are singulated and transported on conveyor belts. Images of the arils are acquired using two cameras to allow estimation of the quality and are then expelled through different outlets according to the category. New control software were developed that synchronise the advance of the conveyor belts, the acquisition of images and the separation by air ejectors, which also includes mechanisms for the synchronisation and communication between the vision and control computers. A new computer vision system has been developed for the inspection of arils that distinguish between arils and raw material by estimating the colour of the objects and then classify the arils by size and colour. The prototype was tested over a six-month period in a Spanish pomegranate producer, with the inspection of about 5 Mg of product. The new prototype achieves the objective of inspecting and sorting pomegranate arils according to their quality, reaching the performance specifications.
引用
收藏
页码:12 / 16
页数:5
相关论文
共 12 条
[1]   Multispectral inspection of citrus in real-time using machine vision and digital signal processors [J].
Aleixos, N ;
Blasco, J ;
Navarrón, F ;
Moltó, E .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 33 (02) :121-137
[2]  
ARANDA JD, 1997, INT WORKSH ROB AUT M, P77
[3]   Citrus sorting by identification of the most common defects using multispectral computer vision [J].
Blasco, J. ;
Aleixos, N. ;
Gomez, J. ;
Molto, E. .
JOURNAL OF FOOD ENGINEERING, 2007, 83 (03) :384-393
[4]   Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm [J].
Blasco, J. ;
Aleixos, N. ;
Molto, E. .
JOURNAL OF FOOD ENGINEERING, 2007, 81 (03) :535-543
[5]   Machine vision system for automatic quality grading of fruit [J].
Blasco, J ;
Aleixos, N ;
Moltó, E .
BIOSYSTEMS ENGINEERING, 2003, 85 (04) :415-423
[6]  
Blasco J, 2007, LECT NOTES COMPUT SC, V4478, P460
[7]   Improving quality inspection of food products by computer vision - a review [J].
Brosnan, T ;
Sun, DW .
JOURNAL OF FOOD ENGINEERING, 2004, 61 (01) :3-16
[8]   The application of a fast algorithm for the classification of olives by machine vision [J].
Diaz, R ;
Faus, G ;
Blasco, M ;
Blasco, J ;
Moltó, E .
FOOD RESEARCH INTERNATIONAL, 2000, 33 (3-4) :305-309
[9]  
GALINDO M, 1997, INT WORKSH ROB AUT M, P89
[10]   Effects of classification methods on color-based feature detection with food processing applications [J].
Lee, Kok-Meng ;
Li, Qiang ;
Daley, Wayne .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2007, 4 (01) :40-51