VeggieVision: a produce recognition system

Author

Bolle, R.M. ; Connell, J.H. ; Haas, N. ; Mohan, R. ; Taubin, G.

Author_Institution

IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA

fYear

1996

fDate

2-4 Dec 1996

Firstpage

244

Lastpage

251

Abstract

The authors present an automatic product 1D system (“VeggieVision”), intended to ease the produce checkout process. The system consists of an integrated scale and imaging system with a user-friendly interface. When a produce item is placed on the scale, an image is taken. A variety of features, color, texture (shape, density), are then extracted. These features are compared to stored “signatures” which were obtained by prior system training (either on-line or off-line). Depending on the certainty of the classification, the final decision is made either by the system or by a human from a number of choices selected by the system. Over 95% of the time, the correct produce classification is in the top four choices

Keywords

feature extraction; image classification; image colour analysis; retail data processing; VeggieVision; automatic product 1D system; color; integrated scale/imaging system; produce checkout process; produce classification; produce recognition system; stored signatures; system training; texture; user-friendly interface; Cameras; Hardware; Humans; Image recognition; Image segmentation; Machine vision; Optical polarization; Optical reflection; Prototypes; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications of Computer Vision, 1996. WACV '96., Proceedings 3rd IEEE Workshop on

Conference_Location

Sarasota, FL

Print_ISBN

0-8186-7620-5

Type

conf

DOI

10.1109/ACV.1996.572062

Filename

572062