tailieunhanh - Color separation Algorithm and Rice identification

This article presents a method to identify good and bad grain and then they will be classified and processed. The algorithm mentioned here will determine the good and bad grain at high speed frame (18500 frames/s), and determine the speed of rice moving. | TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 17, SOÁ K2- 2014 Color separation Algorithm and Rice identification • Phan Huynh Lam • Nguyen Thanh Nam • Pham Van Duy • Nguyen Thien Binh • Le Thanh Son DCSELAB, University of Technology, VNU-HCM (Manuscript Received on December 11th, 2013; Manuscript Revised August 26th, 2014) ABSTRACT: This article presents a method to identify good and bad grain and then they will be classified and processed. The algorithm mentioned here will determine the good and bad grain at high speed frame (18500 frames/s), and determine the speed of rice moving. The identification of better or worse than the threshold used in Keywords: CCD Line, rice sorting, OpenCV. the algorithm are combination of light wavelengths and identify appropriate length of grain. This paper describes the experimental results: the influence of the light wavelength, the effect of imagecapturing speed, identity technique and threshold filtering. 1. INTRODUCTION Rice color separating is the high speed image conducted experiments with different types of processing system (frame> 1000 frames / s), it is .). able to classify many types different colors of rice light (White LED, Halogen, Fluorescence, Blue Substantial work for classifying and (white, yellow, crimson.) to determine the best identifying varieties of grain has been reported. kind of rice that is pure white. . Anami et al., [2] described a method for For identifying accurately and promptly, we use gradation and classification of different grain the CCD line camera system has rate up to 18500 such as wheat, Bengal gram, groundnut, etc. An frame / s [1] with a reference appropriate artificial neural network approach is used in wavelength. We tested the layout system such as the Identification and classification of the bulk Figure 1. One axis will move with high speed to grain samples by . Visen , [3]. Harlick, symbolize the movement of grain, the inspectorial ., .