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Titre du document / Document title

Detection of pinholes in almonds through X-ray imaging

Auteur(s) / Author(s)

KIM S. (1) ; SCHATZKI T. (1) ;

Affiliation(s) du ou des auteurs / Author(s) Affiliation(s)

(1) USDA Agricultural Research Service, Western Regional Research Lab, Albany, California, ETATS-UNIS

Résumé / Abstract

Pinhole insect damage in natural almonds (i.e., in nuts with the brown skin intact) is very difficult to detect on line. For quality reasons, methods to detect and remove such damaged nuts are of great importance. In this study, we explored the possibility of using X-ray imaging to detect pinhole damage in almonds by insects. X-ray film and x-ray line-scanned images of 522 pinhole-damaged almonds were obtained. Of these film images, 505 were successfully digitized to 8 bits by use of a film scanner with a 0.173-mm detector pitch, and 499 of the 505 were collected by a line-scan unit with 0.5-mm pitch photodiodes, again at 8 bits. The pinhole-damaged region appeared slightly darker than the non-damaged region in X-ray negative images. A machine-recognition algorithm was developed to detect these darker regions. The algorithm used first-order (pixel intensity) and second-order (intensity change) information to identify the damaged region. To reduce the number of false positive results due to germ regions in high-resolution images, germ detection and removal routines were also included. With scanned film images, the algorithm showed approximately an 81% correct recognition ratio with only 1% false positives. With line-scanned images, 65% of the pinholes were correctly recognized with less than 12% false positives. The algorithm was very fast and efficient, requiring only minimal computation time. The computation rate, if implemented on line, was estimated to be 66 nuts/s, while the x-ray line scanner could achieve a scan rate of 24 nuts/s.

Revue / Journal Title

Transactions of the ASAE    ISSN  0001-2351   CODEN TAAEAJ 

Source / Source

2001, vol. 44, no4, pp. 997-1003 (15 ref.)

Langue / Language

Anglais

Editeur / Publisher

American Society of Agricultural Engineers, St. Joseph, MI, ETATS-UNIS  (1958-2005) (Revue)

Mots-clés anglais / English Keywords

Nuts

;

Pest

;

Fruit tree

;

Invertebrata

;

Arthropoda

;

Spermatophyta

;

Angiospermae

;

Dicotyledones

;

Rosaceae

;

Almond

;

Insecta

;

Prunus dulcis

;

Experimental study

;

Image analysis

;

Computer vision

;

X ray

;

Detection

;

Damage

;

Quality control

;

Fruit industry

;

Postharvest

;

Mots-clés français / French Keywords

Fruit sec

;

Déprédateur

;

Arbre fruitier

;

Invertebrata

;

Arthropoda

;

Spermatophyta

;

Angiospermae

;

Dicotyledones

;

Rosaceae

;

Amande

;

Insecta

;

Prunus dulcis

;

Etude expérimentale

;

Analyse image

;

Vision ordinateur

;

Rayon X

;

Détection

;

Dégât

;

Contrôle qualité

;

Industrie fruits

;

Après récolte

;

Mots-clés espagnols / Spanish Keywords

Frutos secos

;

Plaga

;

Arbol frutal

;

Invertebrata

;

Arthropoda

;

Spermatophyta

;

Angiospermae

;

Dicotyledones

;

Rosaceae

;

Almendra

;

Insecta

;

Prunus dulcis

;

Estudio experimental

;

Análisis imagen

;

Visión ordenador

;

Rayos X

;

Detección

;

Estrago

;

Control calidad

;

Industria frutas

;

Postcosecha

;

Localisation / Location

INIST-CNRS, Cote INIST : 2869, 35400009431645.0300

Nº notice refdoc (ud4) : 13385883



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