• 제목/요약/키워드: Automatic grading and sorting system

검색결과 19건 처리시간 0.026초

인터넷을 이용한 건표고 등급선별장치의 원격제어 및 관리 시스템 개발 (Development of Remote Control and Management System for Dried Mushroom Grader via Internet)

  • 최태현;황헌
    • Journal of Biosystems Engineering
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    • 제24권3호
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    • pp.267-274
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    • 1999
  • An internet and network based software and related interface have been developed, which can remotely control and manage an on-site operating system. Developed software modules were composed of two parts: monitoring/management modules and control/diagnosis modules were developed for the network status, warehouse, production and selling status. Modules of control with diagnosis were developed for the on-site operating system and interface. Each module was integrated and the whole modules have been tested with an automatic mushroom grading/sorting system which was built in a laboratory. Developed software modules worked successfully without any uncommon situations such as system down caused by the software or data transfer error. Each software module was developed independently in order to apply easily to other existing on-site systems such as rice processing centers, fruit and vegetable sorting, packaging and distribution centers scattered over the country.

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Development of Automatic Peach Grading System using NIR Spectroscopy

  • Lee, Kang-J.;Choi, Kyu H.;Choi, Dong S.
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1267-1267
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    • 2001
  • The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.

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컴퓨터시각과 신경회로망에 의한 표고등급의 자동판정 (Computer Vision and Neuro- Net Based Automatic Grading of a Mushroom(Lentinus Edodes L.))

  • Hwang, Heon;Lee, Choongho;Han, Joonhyun
    • 생물환경조절학회지
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    • 제3권1호
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    • pp.42-51
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    • 1994
  • 대다수 농산물과 마찬가지로 건조표고의 등급판정은 외관특징에 주로 의존한다. 표고 갓의 전후면에 걸친 복잡하고 다양한 외관특징들로 인하여 표고의 등급판정은 임의로 추출한 표고샘플에 대하여 전문가가 수작업으로 판정하고 있으며, 선별작업 역시 전적으로 수작업에 의존하고 있다. 단순한 반복작업으로 보이는 농산물의 등급판정은 사실 시각과 촉각을 위시한 고도의 감각신경계를 통하여 상호 복잡하게 얽혀 들어오는 정보를 지능적으로 처리하는 고기능의 작업이다. 농산물의 경우, 외관특성을 비롯한 물성은 종류별로 그 경계치를 일괄적으로 명확하게 규정할 수 없기 때문에 대개는 오차를 포함한 통계적 접근에 의하여 규정하고 있다. 따라서 농산작업에 있어서는 농산물 물성이 갖는 모호성을 효율적으로 처리할 수 있는 가변적인 작업구조 및 정보처리가 필수적으로 요구된다. 본 연구에서는 인간 뇌의 정보처리 기능을 부분적으로 구현할 수 있는 인공신경회로망을 컴퓨터 시각 시스템에 적용하여 단순 기하도형의 분류 및 표고의 등급판정을 성공적으로 수행하였다. 회로망 입력으로는 컴퓨터시각 시스템을 이용하여 건조표고의 정성적 외관특징을 자동으로 추출한 후 정량화한 특징점 값들을 이용하였다. 신경회로망의 학습은 표본 추출한 등급표고와 이들의 정량적 특징점 값들을 입출력 쌍으로 하여 수행하였다. 학습한 회로망의 등급판정 성능시험은 표본추출한 미지의 표고에 대한 컴퓨터 영상 특징점 값들을 입력하여 수행하였다.

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기계시각에 의한 풋고추 온라인 등급판정 알고리즘 개발 (Development of On-line Grading Algorithm of Green Pepper Using Machine Vision)

  • 조남홍;이수희;황헌;이영희;최승묵;박종률;조광한
    • 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.

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인삼선별의 자동화를 위한 컴퓨터 시각장치 - 등급 자동판정을 위한 영상처리 알고리즘 개발 - (Computer Vision System for Automatic Grading of Ginseng - Development of Image Processing Algorithms -)

  • 김철수;이중용
    • Journal of Biosystems Engineering
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    • 제22권2호
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    • pp.227-236
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    • 1997
  • Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

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영상처리에 의한 계란의 파란 검출 및 선별 (Crack Detection and Sorting of Eggs by Image Processing)

  • 조한근;권양;조상구
    • 한국가금학회지
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    • 제22권4호
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    • pp.233-238
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    • 1995
  • A computer vision system was built to generate images of a single, stationary egg. This system includes a CGD camera, a frame grabber, and incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs viewed from above. Those two values were used as criteria to sort eggs. The coefficients of determination(r$^2$) for the regression equations between weights and those two values were 0.967 and 0.972 in the two sets of experiment. Accuracies in grading were found to be 95.6% and 96.7% as compared with results from sizing by electronic weight scale.

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표고 외관 특징점의 자동 추출 및 측정 (Automatic Extraction and Measurement of Visual Features of Mushroom (Lentinus edodes L.))

  • 황헌;이용국
    • 생물환경조절학회지
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    • 제1권1호
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    • pp.37-51
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    • 1992
  • Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.

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Development of an Automatic Fruit Grader using Computer Image Processing

  • Noh, Sang-Ha;Lee, Jong-Whan-;Hwand, In-Geun
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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    • pp.1292-1301
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    • 1993
  • This study was intended to examine feasibility of sizing and color grading of Fuji apple with black/white image processing system , to develop a device with which the whole surface of an apple could be captured by one camera , to develop an algorithm for a high speed sorting , and to examine the effects of blurring on the performance of the experimental fruit grader.

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흑백영상처리장치를 이용한 과실선별기 개발에 관한 연구(I) - 크기 및 색택 판정 - (Development of a Fruit Grader using Black/White Image Processing System(I) - Determining the Size and Coloration -)

  • 노상하;이종환;이승훈
    • Journal of Biosystems Engineering
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    • 제17권4호
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    • pp.354-362
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    • 1992
  • This study was intended to examine feasibility of sizing and color grading of Fuji apple with black/white image processing system, to develop a device with which the whole surface of an apple could be captured by one camera, and to develop an algorithm for a high speed sorting. The results are summarized as follows : 1. The black/white image processing system used in this study showed a maximum error of 1.3% in area measurement with a reference figure while the focusing point of camera and location of the reference figure were changed within a certain range. 2. As the result of evaluating four automatic image segmentation algorithms with apple images, Histogram Clustering Method was the best in terms of computation time and accuracy. 3. The fast algorithm for analyzing size and coloration of apple was developed. 4. The whole surface of an apple could be captured in an image frame with two mirrors installed on the both sides of the sample. The total area of the image representing the whole surface showed a correlation of 0.995 with the weight of apple. 5. The gray level when a particular band pass filter was mounted on the camera showed high correlation with 'L' and 'a' values of Hunt color scale and could represent the coloration of apple.

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