• 한국의류산업학회지
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• 제13권6호
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• pp.934-942
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• 2011

This study was intended to analyze conventional grading increments and methods for middle-age men's pants, and to suggest new grading guidelines that will enable to improve satisfaction with size and silhouette as a result of combining the concept of grading, which help maintain the ratio and proportion by sizes as one of ready-made apparel's advantages, with body form oriented and aesthetic approaches. In the apparel industry, the current sizing specifications and methods adopted by relevant companies, as well as the characteristics of body forms of men aged 35 to 55 years were comparatively analyzed to find out problems and ultimately to suggest their solutions or improvements. It was considered that as the conventional grading practices used in the industry were customary on the basis of the past experiences, it was required to take the body forms of target consumers into account and also, to reconsider the conventional grading methods. Analyses of sizing and specifications by brands show that 4 to 19 sizes including 82 or 84 as standard size have been produced. Since men's apparel has a large number of sizes with the large range of sizes, grading is critically important. As silhouettes depend on the distribution of grading rule values at each point of increment pattern in the main regions during grading, it is necessary to consider both size grading and form variations. To maintain an appropriate silhouette with keeping the angle of center back line of a pattern, it is desirable to set the ratio of side line part to center part from the crease line to approximately 3:7. It is required to diversify the values of grading rules according to different sizes and pattern regions in consideration for the body forms of key consumers. In addition, if the natural lines of designs and patterns for the width increments of waist circumference and hip circumference, the increments of hip width in pant's front and back panels, the ratio of grading rule values of the right and left sides of crease line, knee circumference, thigh circumference and so on are taken into account, grading will be satisfactory in the all aspects of size, silhouette and ratio.

• Agricultural and Biosystems Engineering
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• 제1권2호
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• pp.106-110
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images. 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc. A total of seven images, that is, one color image form the top of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filtered image and the other is 970 nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results with Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defect and shape were 95.3%, 86% and 88.6%, respectively. Grading time was 0.35 second per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.551-559
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images, 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc., so that a total of seven images, that is, one color image from the top side of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filter image and the other is 970nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results to the Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defective and shape were 95.3%, 86% and 91%, respectively. Grading time was 0.35 sec per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.607-614
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• 1996

A computer vision based automatic intelligent sorting system for dried oak mushrooms has been developed. The developed system was composed of automatic devices for mushroom feeding and handling, two sets of computer vision system for grading , and computer with digital I/O board for PLC interface, and pneumatic actuators for the system control. Considering the efficiency of grading process and the real time on-line system implementation, grading was done sequentially at two consecutive independent stages using the captured image of either side. At the first stage, four grades of high quality categories were determined from the cap surface images and at the second stage 8 grades of medium and low quality categories were determined from the gill side images. The previously developed neuro-net based mushroom grading algorithm which allowed real time on-line processing was implemented and tested. Developed system revealed successful performance of sorting capability of approximate y 5, 000 mushrooms/hr per each line i.e. average 0.75 sec/mushroom with the grading accuracy of more than 88%.

• 한국의류학회지
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• 제27권9_10호
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• pp.1048-1059
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• 2003

This study focusses pattern draft and grading of jeans for women in their 20s, who consume jeans the most. Pattern was drafted based on existing patterns collected from companies. It is different from the existing educational patterns. It suggests new sizing system for twenties referring to sizes used companies and grading rule and method. he results were as follows; 1. Companies manufacture 2-8 sizes and they referred to the Korean Industrial Standards, KS K 0051, for their sizing system. 2. Drawing method for Pattern of the study had following measurements for each part: in the case of waist circumference, front part was W/4+1.5cm, back part was W14+2cm, front hip circumference was H/4-1.5cm, crotch line was the crotch length (practical measurement), hip circumference was (upper crotch line length)/5+0.5cm, front crotch part was 2.7cm, back crotch part was W/5+2.7cm, knee height was (the length of leg)/2+6cm and the circumference of knee and the tip of pants were 40cm. Through the wearing test on the subject of twenties, researched pattern received higher ratings, especially in appearance than the existing pattern. 3. 5 sizes system was made referred to the sizing system of companies and National Anthropometric Survey of Korean in 1997 Grading rule for 12 grading points of front part and 13 grading points of back part was suggested. Results of wearing test on the graded patterns showed high ratings similar to standard size.

• Journal of Biosystems Engineering
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• 제26권2호
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• pp.147-154
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• 2001

In Korea and Japan, dried oak mushrooms are classified into 12 to 16 different categories based on its external visual quality. And grading used to be done manually by the human expert and is limited to the randomly sampled oak mushrooms. Visual features of dried oak mushrooms dominate its quality and are distributed over both sides of the gill and the cap. The 2nd prototype computer vision based automatic grading and sorting system for dried oak mushrooms was developed based on the 1st prototype. Sorting function was improved and overall system for grading was simplified to one stage grading instead of two stage grading by inspecting both front and back sides of mushrooms. Neuro-net based side(gill or cap) recognition algorithm of the fed mushroom was adopted. Grading was performed with both images of gill and cap using neural network. A real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed and implemented to the controller and the performance was verified. Two hundreds samples chosen from 10 samples per 20 grade categories were used to verify the performance of each unit such as feeding, reversing, grading, and discharging unites. Test results showed that success rates of one-line feeding, reversing, grading, and discharging functions were 93%, 95%, 94%, and 99% respectively. The developed prototype revealed successful performance such as the approximate sorting capability of 3,600 mushrooms/hr per each line i.e. average 1sec/mushroom. Considering processing time of approximate 0.2 sec for grading, it was desired to reduce time to reverse a mushroom to acquire the reversed surface image.

• 복식문화연구
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• 제10권4호
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• pp.377-391
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• 2002

The purpose of this study was to research grading work according to the targets of women's wear manufacturers in Korea. For the questionnaire, 91 women's wear brands, which were in higher ranking of sales, were selected, and the age groups were separated into 3: 20's, 30's, and 40's & 50's, according to their customers. The graders of each brand were questioned about 20 items for this research. The results of the questionnaire were as follows: 1 The brands for older women manufactured more sizes and cared more about somatotypes fur grading than other brands did. 2. For upper garments on the basis of bust girth, the numbers of dimensional increments were different depending on the age groups: 9 for 20's, 7 for 30's, and 7 for 40's & 50's. 3. For lower garments on the basis of hip girth, the numbers of dimensional increments were different depending on the age groups: 9 for 20's, 6 for 30's, and 5 for 40's & 50's. 4. As a model size of grading, many brands used the smallest size, but the brands for 40's & 50's also used the second size. 5. The parts needed to be corrected after grading were sleeve ease, armhole, shoulder line, neckline, crotch curve, etc. The grading with CAD system had more correction after grading than hand grading.

• Journal of Biosystems Engineering
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• 제26권6호
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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.

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.8-15
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• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• Journal of Biosystems Engineering
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• 제24권2호
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• pp.153-158
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• 1999

As a basic research for the development of the automatic grading and sorting system for dried oak mushrooms, the device to acquire both cap and gill side images of mushroom has been developed and neural network based side recognition and quality grading has been proposed via inputting both side images. 20 quality grades have been selected considering the requirement of grade classifications imposed by the mushroom company. Developed DC motor driven‘V’type reversing device for the image acquisition of both side images of mushroom showed more than 95% success. Most error was caused by very small size mushrooms with a radius of around 1cm. However, it required a further research to reduce the reversing time. Grading and side recognition were performed via inputting normalized size factors and average gray levels of $8{\times}8$ grids converted from the raw images of both surfaces to the multi-layer back propagation(BP) network. Accuracy of the grading showed about 88.5% and the total grading time including reversing operation was around 2 seconds.