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Color Based Identification and Classification of Boiled Food Grain Images

  • Basvaraj S Anami und Vishwanath C Burkpalli
Veröffentlicht/Copyright: 29. Dezember 2009
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Texture and color are the important features used in identifying objects or regions of interest (ROI) in any image, be it a photomicrograph, an aerial photograph, or a satellite image. We propose a methodology for identification and classification of boiled food grains based on the level of boiling using two color models HSV and L*a*b*, in Indian context. These color models provide good texture definition for any image. The classification is performed at two levels: Level 1 determines the type of grain image and Level 2 estimates the amount of boiling, as full boiled, medium boiled and half boiled. Results show average accuracies of 80% and 96% for first level and 70% and 96% accuracies for second level classifications for HSV and L*a*b*, respectively. The work is applicable to automatic inspection of food preparations in food industry and monitoring, cooking, and serving food in restaurants, hotels and malls by service robots.

Published Online: 2009-12-29

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Heruntergeladen am 30.9.2025 von https://www.degruyterbrill.com/document/doi/10.2202/1556-3758.1669/html
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