New feature extraction method for classification of agricultural products from x-ray images

Ashit Talukder; David P. Casasent; Ha-Woon Lee; Pamela M. Keagy; Thomas F. Schatzki

doi:10.1117/12.336874

14 January 1999 New feature extraction method for classification of agricultural products from x-ray images

Ashit Talukder, David P. Casasent, Ha-Woon Lee, Pamela M. Keagy, Thomas F. Schatzki

Proceedings Volume 3543, Precision Agriculture and Biological Quality; (1999) https://doi.org/10.1117/12.336874
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

Classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non- invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work the MRDF is applied to standard features. The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC data.

Citation Download Citation

Ashit Talukder, David P. Casasent, Ha-Woon Lee, Pamela M. Keagy, and Thomas F. Schatzki "New feature extraction method for classification of agricultural products from x-ray images", Proc. SPIE 3543, Precision Agriculture and Biological Quality, (14 January 1999); https://doi.org/10.1117/12.336874

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