• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.210-216
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• 1997

A study to select ground colors of Fuji apple for maturity index which are needed to standardize grading of the apples is presented. Two extreme colors of immature and fully mature Fuji and Zonagold apples produced in Korea were determined. Various ground colors of Fuji apple between the two extreme colors were collected and classified by human vision and colors of Fuji apple for maturity index were selected from the classification. Coordinates of the selected colors in xy chromaticity diagram were determined by spectrophotometers to define them in a standard coordinate system. Coordinates of the colors in r-g chromaticity diagram using a color machine vision system were also determined to use the colors in apple grading by the machine vision system. Grading Fuji apples using the machine vision system was performed and result of the grading was compared with Ending results of human vision and colorimeter. The comparison was performed with the same Fuji apple samples and showed 65% md 75% of same grades, respectively, as the grades determined by the machine vision system. Differences of fading performance between the compared three grading methods were explained as mainly because of the differences of observation area of the grading methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.103-104
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• 2007

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.3
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• pp.317-322
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• 1998

Generally, the conventional fish size grading methods just adopt the mechanical technique. So the grading methods have a problem such that the graded fish is easy to hurt on the skin and in the internal organs. In this paper, a fish size grading machine is developed using an image processing method. The grading method is based on the principal axis theorem. The length and projected area of a fish are obtained by getting the principal axis and the product of inertia moment on the captured image of a target fish. The developed machine uses an uncontact technique that the target fishes go through the front side of the CCD camera. So the above stated problem can be improved. The performance of this method is discussed with the experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.10
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• pp.897-904
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• 2008

Egg grading machine is used in poultry raising industry to classify eggs by their weight and to pack up them. Packer holder mechanism is a main part of the egg grading machine, of which role is to take eggs fallen from conveyor belt, and afterward to transfer eggs vertically to mold tray. The vertical motion of packer holder is usually driven by slider-crank mechanism or cam. This paper describes development of the cam in packer holder based on kinematic analysis of packer holder mechanism and measurement of acceleration and noise of the cam to verify performance of it. Several cams that are designed and manufactured by the author of this paper according to different design specification are compared to determine the best solution for egg transfer in the packer holder mechanism.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.140-145
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• 2001

Lasting machines for shoe manufacturing are continuously developed with the aid of automation and Computer Aided Manufacturing (CAM). Adaptive lasting machine and CAD data of a shoe last are inevitably introduced for the labor-free manufacturing process. Recently, method for the CAD datarization of a shoe last is suggested using finite element mesh system. Initial set up data and control data of machine parts are required for the adaptive lasting machine. For the efficient process, grading of those data is essential to minimize data storage and production costs. In this paper, bonding lines are extracted from the CAD data of a shoe last and graded by the geometric grading system. Tension spline method is adopted for the interpolation of last CAD data. The results are compared with the results from the arithmetic grading system that is widely adopted in the shoemaking companies.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.96-104
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• 2008

An egg grading machine is composed of many mechanisms of which functions are to carry eggs to the bucket in that sensors are located to categorize eggs by their weight, to transfer eggs from the basket of packer holder to the mold tray, to feed the mold tray dispenser after egg chairs are filled with eggs. This paper deals with the analysis and new design of packer holder mechanism of which function is transfer eggs vertically from the bucket conveyor to the mold tray dispenser. Egg is fragile to impact so in designing packer holder mechanism it is necessary to estimate moving speed, acceleration and impact when eggs are touched by any links of mechanism and mold tray dispenser. A new packer holder mechanism is proposed in this paper, which use quick return mechanism composed of 6 links with pin and contact joints.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.1-9
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• 2002

Garlic is one of the major seasoning vegetables in Korea and consumed mostly in a form of peeled cloves. Conventional Korean standards for garlic grading consist of four classes according to the size of bulb and its shape. Sorting and grading of garlic are manually done but could be in the process of automated mechanization using machine vision system in the near future. The proportion of mass of cloves in a garlic bulb to the volume of the bulb (g/ml) was determined to find out the best way of representing both the quantity and quality of cloves in each bulb. Garlic bulb was assumed as an ellipsoid and its major and minor axis and its height were measured to calculate its volume. The mass proportions and density of a garlic bulb and cloves were measured for four domestic varieties of garlic to propose it as a standard for Korean garlic grading machine.

• Journal of Biosystems Engineering
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• v.22 no.1
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• pp.30-40
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• 1997

A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.514-523
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• 2006

Production of green pepper has been increased due to customer's preference and a projected ten-year boom in the industry in Korea. This study was carried out to develop an automatic grading and sorting system for green pepper using machine vision. The system consisted of a feeding mechanism, segregation section, an image inspection chamber, image processing section, system control section, grading section, and discharging section. Green peppers were separated and transported using a bowl feeder with a vibrator and a belt conveyor, respectively. Images were taken using color CCD cameras and a color frame grabber. An on-line grading algorithm was developed using Visual C/C++. The green peppers could be graded into four classes by activating air nozzles located at the discharging section. Length and curvature of each green pepper were measured while removing a stem of it. The first derivative of thickness profile was used to remove a stem area of segmented image of the pepper. While pepper is moving at 0.45 m/s, the accuracy of grading sorting for large, medium and small pepper are 86.0%, 81.3% and 90.6% respectively. Sorting performance was 121 kg/hour, and about five times better than manual sorting. The developed system was also economically feasible to grade and sort green peppers showing the cost about 40% lower than that of manual operations.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.571-578
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• 2001

Production of green pepper has increased for ten years in Korea, as customer's preference of a pepper tuned to fiesta one. This study was conducted to develop an on-line fading algorithm of green pepper using machine vision and aimed to develop the automatic on-line grading and sorting system. The machine vision system was composed of a professive scan R7B CCD camera, a frame grabber and sets of 3-wave fluorescent lamps. The length and curvature, which were main quality factors of a green pepper were measured while removing the stem region. The first derivative of the thickness profile was used to remove the stem area of the segmented image of the pepper. A new boundary was generated after the stem was removed and a baseline of a pepper which was used for the curvature determination was also generated. The developed algorithm showed that the accuracy of the size measurement was 86.6% and the accuracy of the bent was 91.9%. Processing time spent far grading was around 0.17 sec per pepper.