• Journal of Biosystems Engineering
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• 제31권6호
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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.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.513-520
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• 2000

An integrated grader which measures soluble solid content, color and weight of fresh apples was developed by NAMRI. The prototype grader consists of the near infrared spectroscopy and machine vision system. Image processing system and an algorithm to evaluate color were developed to speed up the color evaluation of apples. To avoid the light glare and specular reflection, an half-spherical illumination chamber was designed and fabricated to detect the color images of spherical-shaped apples more precisely. A color revision model based on neural network was developed. Near-infrared(NIR) spectroscopy system using NIR reflectance method developed by Lee et al(1998) of NAMRI was used to evaluate soluble solid content. In order to observe the performance of the grader, tests were conducted on conditions that there are 3 classes in weight sorting, 4 classes in combination of color and soluble solid content, and thus 12 classes in combined sorting. The average accuracy in weight, color and soluble solid content is more than about 90 % with the capacity of 3 fruits per second.

• Journal of Biosystems Engineering
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• 제24권1호
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• pp.67-74
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• 1999

A prototype cut-flower sorter was developed and tested for its performance with five varieties of roses. Support plates driven by a chain mechanism transported the roses into an image inspection chamber. Color image processing algorithms were developed to evaluate the length, thickness, and straightness of stem and color, height, and maturity of bud. The average absolute errors of the system for the measurements of stem length, stem thickness, and height of bud were 19.7 mm, 0.5 mm, and 3.8 mm, respectively. The results of classification by the sorter were compared with those of a human inspector for straightness of stem and maturity of bud. The classification error for the straightness of stem was 8.6%, when both direct image and reflected image by a mirror were analyzed. The accuracy in classifying the maturity of bud varied among the varieties, the smallest for‘Nobless’(1.5%) and the largest for‘Rote Rose’(13.5%). The time required to process a rose averaged 2.06 seconds, equivalent to the capacity of 1,600 roses per hour.

• 자원리싸이클링
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• 제20권1호
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• pp.28-36
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• 2011

국내의 경우 내화재는 일정 기간이 지나면 대부분 폐기 처분되고 있으며, 폐기되는 내화재의 50% 이상이 탄화되지 않은 상태이다. 본 연구에서는 내화재를 색상인식 방법으로 선별하여 재활용 가능성을 검토하였다. 선별기 광원의 색온도가 자연광에 가까운 6,500K에서 순도 97.2%의 회수물을 얻었으며, 자연광에 가까울수록 주변 광원의 간섭이 적어 선별효율이 우수한 것으로 조사되었다. 실험결과 투입 컨베이어 벨트의 속도 800 mm/sec에서 순도 98.8%, 회수율 98.1%로 조사되었으며, 시료크기 20~30 mm에서 순도 및 회수율은 각각 98.2%, 98.4%로 조사되었다. 회수물의 순도 및 선별효율은 컨베이어 벨트의 속도가 느릴수록, 시료의 크기가 클수록 향상되는 것으로 조사되었다. 그러나, 본 색상 자동선별 시스템의 처리용량 및 폐내화재의 재활용성 등을 고려할 경우 최적의 선별조건은 색온도 6,500K, 컨베이어 벨트 속도 1,000 mm/sec, 시료 크기 20mm이하인 것으로 판단된다. 카메라 해상도를 고정하고 인지 영역을 좁게 하여 시료 크기 -10 mm, 벨트컨베이어 속도 1,000 mm/sec에서 순도 97%이상, 회수율 및 선별효율이 각각 98%, 96%이상인 것으로 나타났으며, 동일해상도에서 인지영역이 좁을수록 순도 및 선별효율을 높일 수 있는 것으로 조사되었다.

• Journal of Biosystems Engineering
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• 제30권3호
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• pp.172-178
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• 2005

Grading and sorting an indeterminate form of agricultural products such as sweet potatoes and potatoes are a labor intensive job because its shape and size are various and complicate. It costs a great deal to sort sweet potato in an indeterminate forms. There is a great need for an automatic grader fur the potatoes. Machine vision is the promising solution for this purpose. The optical indices for qualifying weight and appearance quality such as shape, color, defects, etc. were obtained and an on-line sorting system was developed. The results are summarized as follows. Sorting system combined with an on-line inspection device was composed of 5 sections, human inspection, feeding, illumination chamber, image processing & control, and grading & discharging. The algorithms to compute geometrical parameters related to the external guality were developed and implemented for sorting the deformed sweet potatoes. Grading accuracy by image processing was $96.4\%$ and the processing capacity was 10,800 pieces per hour.

• 응용통계연구
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• 제16권1호
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• pp.129-140
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• 2003

본 논문은 통계적 영상처리를 이용하여 과일 선별 시스템을 개발하고자 한다. 히스토그램으로부터 과일 영상의 색깔에 대한 분포를 파악하고 이 표본 위치문제에서 Wilcoxon 검정을 이용하여 에지를 검출한다. 체인코드로부터 과일 영상의 면적, 둘레, 장ㆍ단축의 길이와 원형도 등 기하학적 특성값을 얻는다. 우리는 과일에 대한 영상실험을 통하여 통계적 에지검출 방법에 토대를 둔 시스템과 기존의 Sobel 연산자에 토대를 둔 시스템과의 비교 분석한다.

• 융합신호처리학회논문지
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• 제21권4호
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• pp.154-161
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• 2020

본 논문에서는 인간의 노력을 줄이고 정확성을 높이기 위해 사과의 색을 기반으로 하는 분류 시스템을 제안하였다. 제안된 분류 시스템은 카메라, 모터 및 라즈베리 파이로 구성되어 있고, 미성숙, 성숙, 익은 등으로 총 4가지 종류의 사과를 분류할 수 있다. 시장에서 다양한 종류의 사과를 100개 구입하여 무작위로 선택하여 평가하였다. 정확도는 95%였고 처리 시간은 사과당 약 8초였다. 제안한 시스템은 인력 감축에 유용할 것으로 예상된다.

• 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.

• 한국정보통신학회논문지
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• 제21권9호
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• pp.1681-1688
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• 2017

본 논문에서는 FPGA와 Nor-Flash를 사용하여 컬러 라인 스캔 카메라를 위한 고속 신호처리 하드웨어 시스템을 구현하였다. 기존의 시스템에서는 소프트웨어를 기반으로 한 고속 DSP가 적용되어 왔고 주로 RGB 개별 논리에 의해 결함을 검출하는 방법이었지만 본 논문에서는 RGB-HSL 변환기, FIFO, HSL 풀-컬러 결함 디코더 및 이미지 프레임 버퍼로 구성된 하드웨어 기반의 결함 검출기를 제안하였다. 결함 검출기는 RGB에서 HSL로의 색상 공간 변환을 위한 하드웨어 기반 룩업테이블과 4K HSL 풀-컬러 결함 디코더로 구성되어 있다. 또한 단일 라인 데이터 기반의 로컬 픽셀 처리 대신 2차원 배열 구조의 이미지 단위 처리를 위해 라인 데이터 축적용 이미지 프레임을 포함한다. 설계된 시스템을 기존의 곡물 선별기에 적용하여 땅콩을 대상으로 선별해 본 결과 효과적임을 알 수 있었다.