Title :
Non-destructive Identification of unmilled rice using digital image analysis
Author :
Punthumast, Papol ; Auttawaitkul, Yingrak ; Chiracharit, Werapon ; Chamnongthai, Kosin
Author_Institution :
Dept. of Appl. Sci., Bansomdejchaopraya Rajabhat Univ., Bangkok, Thailand
Abstract :
In this paper, digital image analysis is applied for non-destructive classification of rice and sticky rice seeds that are mixed together. It is a difficult task because of the similar surface color of the seeds. This paper presents an automatic classification method based on RGB color features. Hardware of image capturing is designed using back light source in order to maximize the contrast between the rice seeds and their background. RGB histogram is then calculated. The rule of classification between rice seed and sticky rice seed are created. Almost 97% of rice seeds are identified correctly. The correct classification rates for two rice varieties are: rice seeds `Jasmine´ 96.34% and sticky rice seeds 100%.
Keywords :
agricultural products; feature extraction; image classification; image colour analysis; RGB color features; RGB histogram; agricultural product; back light source; contrast maximization; digital image analysis; image capturing; nondestructive rice classification; nondestructive unmilled rice identification; Digital images; Ear; Educational institutions; Histograms; Image color analysis; Production; Standards; Digital image processing; Indentification of rice seed; RGB color model;
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2012 9th International Conference on
Conference_Location :
Phetchaburi
Print_ISBN :
978-1-4673-2026-9
DOI :
10.1109/ECTICon.2012.6254334