Monitoring geometric characteristics of rice during processing by image analysis system and micrometer measurement

A b s t r a c t. Variations of the geometric characteristics of three Iranian rice varieties, namely Tarom Mahalli, Fajr and Neda, at different processing levels were determined using micrometer and image processing methods. The results obtained by both procedures showed that the geometric characteristics of all three varieties ie length, width, height and projected area, are decreased and the sphericity increased by removing the outer and the brownish layers. The relationships between the micrometer data and the image processing ones were obtained linearly as represented by regression equations. It was found that the micrometer data are underestimated for all the geometric factors and that the true size and sphericity ie ones obtained using image analysis, can be estimated with root mean square error (RMSE) of less than 6% from the dimensional features provided by micrometer procedure. K e y w o r d s: rice, geometric characteristics, micrometer measurement, image processing

[1]  B. K. Yadav,et al.  Monitoring milling quality of rice by image analysis , 2001 .

[2]  B. K. Yadav,et al.  Modeling changes in milled rice (Oryza sativa L.) kernel dimensions during soaking by image analysis , 2007 .

[3]  Da-Wen Sun,et al.  Recent developments in the applications of image processing techniques for food quality evaluation , 2004 .

[4]  I. Arana,et al.  Physical and mechanical properties in rice processing , 2007 .

[5]  M. Analla,et al.  Model validation through the linear regression fit to actual versus predicted values , 1998 .

[6]  Akio Matsuzaki,et al.  Two-dimensional image analysis of the shape of rice and its application to separating varieties , 1996 .

[7]  N. Mohsenin.  Physical properties of plant and animal materials , 1970 .

[8]  B. K. Yadav,et al.  Dimensional changes in milled rice (Oryza sativa L.) kernel during cooking in relation to its physicochemical properties by image analysis , 2007 .

[9]  G. Dalen.  Determination of the size distribution and percentage of broken kernels of rice using flatbed scanning and image analysis , 2004 .

[10]  M. A. Shahin And S.J. Symons,et al.  Lentil type identification using machine vision , 2003 .

[11]  J. Jannink,et al.  Evaluation of Oat Kernel Size Uniformity , 2004 .

[12]  Edo Gerkema,et al.  Magnetic resonance imaging of single rice kernels during cooking. , 2004, Journal of magnetic resonance.

[13]  N. I. Klenin,et al.  Agricultural machines : theory of operation, computation of controlling parameters, and the conditions of operation , 1985 .

[14]  S. Razavi,et al.  Effect of hulling and milling on the physical properties of rice grains , 2008 .

[15]  M. G. Varnamkhasti,et al.  Some physical properties of rough rice (Oryza Sativa L.) grain , 2008 .