Endmember extraction is the key step in the mixed pixel decomposition for hyperspectral images. In view of the larger Markov property of endmember error in the sequence endmember extraction algorithm, which affects the endmember extraction accuracy, we propose an endmember extraction algorithm with three endmembers as a group based on Gram–Schmidt orthogonalization. According to the convex geometry theory, the spectral characteristic and the geometrical property of simplex in feature space have been analyzed, and the idea of group endmember extraction was introduced to reduce the Markov property of the endmember error, improving the endmember extraction accuracy accordingly. The orthogonal vector was searched by Gram–Schmidt orthogonalization and the image was projected to the orthogonal vector, so as to eliminate the effect of the extracted endmembers. The energy function was used as a measure index of the similarity for spectral vectors of different ground objects, and the measure index was used to determine the endmember. The algorithm was verified by using simulation data and real data. The experimental results indicated that the proposed algorithm may extract endmember automatically, and the corresponding endmember extraction accuracy was better than other algorithms.
As the improvement of people's living standard, more and more is required of the superior quality dairy products. An important indicator that gets more and more attention to measure the quality of dairy products is ingredient content of nutrients in dairy products. One of main component of milk, the concentration of milk fat is of great significance for light scattering measurements. The photomicrograph of the different homogeneous state of milk fat solution with is different concentrations obtained by using high magnification optical microscope. And the particle size distribution of different homogeneous state and different concentrations of milk fat solution are analyzed. Based on the principle of light scattering technique for the detection of milk composition, as well as analysis of the physical and chemical properties of milk fat solution, the energy spectrum, absorption spectrum, the transmittance spectrum of the different homogeneous state and the different concentrations of milk fat solution are determined by the dual-beam spectrophotometer (TJ270-60). Then the effects of fat solution concentration, particle size distribution and homogeneous state on the light scattering intensity are analyzed. Furthermore, it is derived the relationships among milk fat solution concentration with energy, absorption and transmittance based on experimental results. This study will bring a progress in processing quality control of product, and contribute to promote the development of China's dairy industry for bringing practical significance and great economic benefits.
Developed an experimental device for rapid and accurate detection of milk macromolecular content. This device developed based on laser scattered through principle, the principle use of the ingredients of the scattered light and transmitted light ratio characterization of macromolecules. Peristaltic pump to achieve automatic input and output of the milk samples, designing weak signal detection amplifier circuit for detecting the ratio with ICL7650. Real-time operating system μC / OS-II is the core design of the software part of the whole system. The experimental data prove that the device can achieve a fast real-time measurement of milk macromolecules.
This paper presents a new method to measure the constituents of the milk, which uses the scattered light to transmitted
light rate of the laser(called s-t rate for short) to detect the protein and fat content of the milk. The basic theory is
discussed in the test in detail and the feasibility of the plan is analyzed. A relation curve between the fat and protein of
milk and the ratio is built by multiple linear regression method. The uncertainty of the result is mentioned in the paper.
Although many methods, such as bacteria plate count, flow cytometry and impedance method have been broadly used in the dairy industry to quantitate bacteria numbers around the world, none of them is a quick, low cost and easy one. In this study, we proposed to apply the color difference theory in this field to establish a mathematic model to quantitate bacteria number in fresh milk. Preliminary testing results not only indicate that the application of the color difference theory to the new system is practical, but also confirm the theoretical relationship between the numbers of bacteria, incubation time and color difference. The proof of the principal study in this article further suggests that the novel method has the potential to replace the traditional methods to determine bacteria numbers for the food industry.
Accurate grading is necessary to ensure the quality of tiles. The quantity of color difference is an important base for grading tiles. For this reason it is necessary to quantify the color differences of tiles. This paper presents a new method of using computer vision technology to measure color differences tiles. It uses CCD image sensors to obtain color images of tiles. The images are then processed with computer to produce the RGB of the color image. The image is then converted from RGB space to CIE1976L*a*b* color space. The character colors are then obtained. The color differences is then determined based on the character colors. A measure system and the color difference computing software were designed. Results from experiments were also given in this paper that color difference values with the different color index are larger than the same color index. The experimental results show that this measuring method can be used for real-time measuring for ceramic tiles.
A novel method to measure the total amount of bacteria in raw milk is introduced in this paper. This method involves optics, color theory and biology. In this method the total amount of bacteria in raw milk is measured according to the color change caused by chemical reaction. The study proves that the total amount of bacteria in raw milk can be measured by this method with high speed and accuracy. Besides, this method is easy operating and very economical. These qualities will surely make it a favorite in the measurement of the total amount of bacteria in raw milk in the future.
Recently, many researches on sensors have focused on sensor functions, but a few of them on sensor reliability. Screen technique for a sensor is important for ensuring the quality of a sensor. In the previous screen methods, the screen time is determined empirically and no suitable theory could apply for it, especially, in developing a new product. The method presented here can determine screen time quickly. In this paper, the relation between reliability life distribution of a sensor with initial failure and screen time was discussed. The failure data from life distribution's corner was dealt with computer and the life distribution curve was inferred. Finally, the screen time was determined by the study of the life distribution. To further interpret the new method, a practical example was given and a satisfy result was obtained.
How to reliably deduce life distribution of sensors is one of the practical problems in engineering. The methods currently used either lack accuracy or can not be applied until extensive test data are available. In this paper, a method combining with graphical estimation and parameter estimation has been proposed to solve this problem. Based upon the conventional methods and the theories described in this study, we have developed a computer software to deduce life distribution for engineering applications. A practical example was also given to show how the program performs statistical inference of life distribution model of sensors. By comparing the distributions, an optimum life distribution can be selected and a fit straight line and distribution parameters can be acquired. Key words: sensor, reliability, life disthbution, statistical inference.