• Journal of Biosystems Engineering
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• v.20 no.4
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• pp.376-382
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• 1995

This study was intended to develop more reliable fruit sorting algorithm regardless of the feeding positions of fruits by using the neural network in which various information could be included as input data. Specific objectives of this study were to select proper input units in the neural network by investigating the features of input image, to analyze the sorting accuracy of the algorithm depending on the feeding positions of Fuji apple and to evaluate the performance of the algorithm for practical usage. the average value in color grading accuracy was 90%. Based on the computing time required for color grading, the maximum sorting capacity was estimated to approximately 10, 800 apples per hours. Finally, it is concluded that the neuro-net based color sorting algorithm developed in this study has feasibility for practical usage.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.231-234
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• 2003

This paper describes the structure, operation, image processing, and decision making techniques of a color machine vision system designed for the automatic sorting of soybeans. The system consists of feeder, conveyor belt, line-scan camera, lights. ejector, and a PC Unlike manufactured goods, agricultural products including soybeans have quite uneven features. The criteria for sorting good and bad beans also vary depending on inspectors. We tackle these problem by letting the system learn the inspecting parameters from good samples selected manually by a machine user before running the system for sorting. Real-time processing has another importance In the design. Four parallel DSPs are employed to increase the processing speed. When the designed system was tested with real soybeans and the result was successful.

• Journal of Biosystems Engineering
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• v.32 no.2 s.121
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• pp.130-135
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• 2007

An on-line real time grading and sorting system for dried oak mushrooms was developed for on-site application. Quality grades of the mushrooms were determined according to an industrial specification. Three dimensional visual quality features were used for the grading. A progressive color computer vision system with white LED illumination was implemented to develop an algorithm to extract external quality patterns of the dried oak mushrooms. Cap (top) and gil (stem) surface images were acquired sequentially and side image was obtained using mirror. Algorithms for extracting size, roundness, pattern and color of the cap, thickness, color of the gil and amount of rolled edge of the dried mushroom were developed. Utilizing those quality factors normal and abnormal ones were classified and normal mushrooms were further classified into 30 different grades. The sorting device was developed using microprocessor controlled electro-pneumatic system with stainless buckets. Grading accuracy was around 97% and processing time was 0.4 s in average.

• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.279-286
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• 2001

The purpose of this study were to organize a sorting system, to develop an algorithm of image processing for the shape sorting, and to finally develop a scientific and objective shape sorting system of Korean Red-Ginseng for mechanization of the shape sorting. The results of this study are followed. 1. The shape sorting system of Korean Red-Ginseng consists of a control computer, a color CCD camera(WV-CP4110) for image processing, an image processing board(DT3153), and an image acquisition unit. 2. Many image processing skill, such as sliding, stretching, threshold, binary and D$\sub$t/ were used to analyze the shape sorting factors of Korean Red-ginseng. 3. The sorting accuracy of the shape sorting system for the Korean Red-Ginseng was 74.7%. It is 21.1% lower than that of human inspector. Although the system has low accuracy, using more cameras may improve its sorting accuracy.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.100-105
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• 2000

Quality sorting of cut flowers is very essential to increase the value of products. There are many factors that determine the quality of cut flowers such as length, thickness, and straightness of stem, and color and maturity of bud. Among these factors, the straightness of stem and the maturity of bud are generally considered to be more difficult to evaluate. A prototype grading and sorting machine for cut flowers was developed and tested for a rose variety. The machine consisted of a chain-drive feed mechanism, a pneumatic discharge system, and a grading system utilizing color image processing and neural network. Artificial neural network algorithm was utilized to grade cut roses based on the straightness of stem and maturity of bud. Test results showed 89% agreement with human expert for the straightness of stem and 90% agreement for the maturity of bud. Average processing time for evaluating straightness of the stem and maturity of the bud were 1.01 and 0.44 second, respectively. Application of neural network eliminated difficulties in determining criteria of each grade category while maintaining similar level of classification error.

• Resources Recycling
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• v.28 no.2
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• pp.23-30
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• 2019

An color sorting technique was introduced to recycle End-of-life automobile shredded bumpers. The color sorting is a innovate method of separating the differences in the color of materials which are difficult to separate in gravity and size classification by using a camera and an image process technique. Experiments were planned and optimal conditions were derived by applying BBD (Box-Behnken Design) in the reaction surface method. The effects of color sensitivity, feed rate and sample size were analyzed, and a second-order reaction model was obtained based on the analysis of regression and statistical methods and $R^2$ and p-value were 99.56% and < 0.001. Optimum recovery was 94.1% under the conditions of color sensitivity, feed rate and particle size of 32%, 200 kg/h, and 33 mm respectively. The recovery of actual experiment was 93.8%. The experimental data agreed well with the predicted value and confirmed that the model was appropriate.

• Journal of the Korean Society of Visualization
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• v.6 no.2
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• pp.20-27
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• 2008

The color sorting technique utilizing the image processing method is very applicable tool to analyze motion of a free-falling object in many agricultural and industrial research fields. In the present study, we have developed an image processing system and algorithm to sort good quality rice grains effectively from the bad ones. The system employs a high speed rate line-scan CCD camera with 2K-pixels and worked with a high speed DSP and FPGA in-line. It can accumulate acquired line-scan image data and visualize each grain image clearly. As a result, we can easily calculate the number of pixels occupied by grain(=grain size), gray level and its correct position by visualizing grain images rapidly.

• Korean Journal of Agricultural Science
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• v.37 no.2
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• pp.303-308
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• 2010

Surface color is the most important quality factor for the grade evaluation of cherry tomato. Color is one of the representative indicators for the maturity which is closely related to the internal quality of cherry tomato, such as firmness, sugar content, and acidity. This study was carried out to investigate the relationship between surface color and internal quality of cherry tomatoes harvested from both hydroponic and soil culture at different ripening stages. To calculate the color values of cherry tomatoes an automatic color imaging system was constructed. A specially designed image processing algorithm for the color measurement was developed. The color values of L*, a*, b* were calculated from the initial color values of RGB and then compared with the internal quality. Statistical analyses indicated that the internal quality was more highly correlated with the surface color than size of cherry tomatoes. Color image features were also investigated to detect external damage of cherry tomatoes. The value of (R value - R mean value)/R mean value was the most effective image feature for the detection of damaged areas on the surface of cherry tomatoes. The results of this study demonstrated the feasibility of color sorting process as an alternative of the conventional drum type size sorting system for cherry tomato industry.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.382-395
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• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.

• Resources Recycling
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• v.17 no.6
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• pp.43-49
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• 2008

In this study, a scrap sorting system using a color recognition method has been developed to automatically sort out specified materials from a mixture, and its application as been examined in the separation of Cu and other non-ferrous metal parts from a mixture of iron scraps. The system is composed of three parts; measuring, conveying and ejecting parts. The color of scrap surface is recognized by the measuring part consisting of a line-scan camera, light sources and a frame grabber. The recognition is program-controlled by a image processing algorithms, and thus only the scrap part of designated color is separated by the use of air nozzles. In addition, the light system is designed to meet a high speed of sorting process with a frequency-variable inverter and the air nozzled ejectors are to be operated by an I/O interface communication with a hardware controller. In the functional tests of the system, its efficiency in the recognition of Cu scraps from its mixture with Fe ones reaches to more than 90%, and that in the separation more than 80% at a conveying speed of 25 m/min. Therefore, it is expected that the system can be commercialized in the industry of shredder makers if a high efficiency ejecting system is realized.