NDLI: Chile identification for metrics in the chile industry

Content Provider	IEEE Xplore Digital Library
Author	Muguira, M.R. Salton, J.R. Novick, D.K. Schwebach, J.N. Wilson, C.W.
Copyright Year	2005
Description	Author affiliation: Intelligent Syst. & Robotics Center, Sandia Nat. Labs., Albuquerqueu, NM, USA (Muguira, M.R.; Salton, J.R.; Novick, D.K.; Schwebach, J.N.; Wilson, C.W.)
Abstract	This paper presents a novel approach to identify chile pods in two dimensional images of chile harvests in order to quantitatively evaluate harvesting and cleaning systems. Chilies vary greatly in shape, color, and texture throughout the season and within varieties and thus pose a unique challenge compared to the identification of other more uniform objects. Since chilies do not have distinct point features typically exploited in object recognition algorithms, a normalized shape distribution function was used to describe each object's general shape. 486 harvest object images were collected throughout the season and then placed in categories. Representative shape functions were derived from chilies in a given category and the other chilies, stems, and leaves were compared to each class. Sample shape distributions were found to provide a robust signature to discriminate among chile pods and harvest trash objects.
Starting Page	3118
Ending Page	3123
File Size	892332
Page Count	6
File Format	PDF
ISBN	0780392981
DOI	10.1109/ICSMC.2005.1571625
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Distribution functions Intelligent robots Costs Textile industry System testing Moisture Intelligent systems Service robots Laboratories classification Shape distribution functions shape analysis image analysis natural shapes object identification
Content Type	Text
Resource Type	Article

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