keivan ansari

A condition that must be satisfied for digital printers in a color management system is converting device-dependent color values into device-independent color values by a transfer model of high-quality performance. Usually, each transfer model is initially trained with some specified samples as a training set before being tested. In the present study, color charts with different quantities of color patches in an RGB space were selected and printed as training groups.  The spectral reflectances of all samples in printed color charts were measured and converted to an XYZ color space under a standard observer/illuminant combination. Using a matrix method, the RGB to XYZ transformation matrices were obtained with the algebraic operation of different degrees of polynomials and the least-square errors for the training groups.Similar operations were also performed for the well-known ProfileMaker software, which is based on a look-up table method. Finally, the statistical values of color difference (DE2000) were calculated between the actual XYZ from the printed color charts, the predicted XYZ from the matrix method, and those predicted from the ProfileMaker software. The ProfileMaker software showed a significantly lower color difference near the perception threshold for the specified training samples.

Raw cane sugar is the one of the most important products in sugar industry. Quality characteristics of raw sugar are the main influence factor in type and quality of refined sugars. The purpose of this research was to find agrrement between the CIE color coordinates and certain quality parameters of various imported raw cane sugar samples. The spectral reflectance of such raw sugar samples were determined with the aid of a spectrophotoradiometer in the range 380 to 780 nm and were then converted to their corresponding CIE color coordinates. The correlation between such color coordinate values and certain quality parameters of samples such as; ash content, sucrose, invert sugar, color solution, pH, starch, dextran content, moisture and refractive index were determined. Results show good to very good correlations between some quality parameters such as starch content, ash content and color solution and various CIE color coordinates values such as L*, a*, b*, C*, h, X, Y, Z, x, y and Y.I.

Sugar beet is considered as a one of the strategic industrial plant and the main source of sugar production in Iran and the world''s. The present study was carried outduring the operation period timein 1392 on sugar beet sent to Hamedan sugar factory. The images of sugar beet samples was obtained using flat-bed scanner. Then the various characteristics of images¡ such as area of sugar beet¡ were determined using MATLAB software. The physicochemical analysis such as determining of sugar content¡ sodium¡ potassium and nitrogen was done. Result shows that some physicochemical properties are in related to the area of sugar beets. For instance¡ the correlation between area and sugar content¡ white sugar content¡ extraction sugar coefficient (ESC) and molasses was (R2= - 0.696)¡ (R2= - 0.724)¡ (R2= -0.679) and (R2= 0.459)¡ respectively. According to these results¡ it can be concluded that the decrease in sugar content and increase the amount of impurities in sugar beet¡ was correlated with sugar beet area¡ and by increasing in the size and area of sugar beet¡ the sugar content was reduced and the impurities was increases.