• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.69-74
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• 2004

In this paper, we propose a novel method for improving defect-detection performance based on reconstruction of line-scan camera images using both the projection profiles and color space transform. The proposed method consists of RGB region segmentation, representative value reconstruction using the tracing system, and Y image reconstruction using color-space transformation. Through experiments it is demonstrated that the performance using the reconstructed image is better than that using aerial image for LCD surface inspection.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1681-1688
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• 2017

In this paper, we implemented a high-speed signal processing hardware system for Color Line Scan Camera using FPGA and Nor-Flash. The existing hardware system mainly processed by high-speed DSP based on software and it was a method of detecting defects mainly by RGB individual logic, however we suggested defect detection hardware using RGB-HSL hardware converter, FIFO, HSL Full-Color Defect Decoder and Image Frame Buffer. The defect detection hardware is composed of hardware look-up table in converting RGB to HSL and 4K HSL Full-Color Defect Decoder with high resolution. In addition, we included an image frame for comprehensive image processing based on two dimensional image by line data accumulation instead of local image processing based on line data. As a result, we can apply the implemented system to the grain sorting machine for the sorting of peanuts effectively.

• 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.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.761-771
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• 2009

Detecting defects on FPD (Flat Panel Display) color filter before the full panel is made is important to reduce the manufacturing cost. Among many types of defects, the low contrast blemish such as Suzi Mura is difficult to detect using standard CCD cameras. Even skilled inspectors in the inspection line can hardly identify such defects using bare eyes. To overcome this difficulty, point spectrometer has been used to analyze the spectrum to differentiate such defects from normal color filters. However, scanning ever increasing-size color filters by a point spectrometer takes too long time to be used in real production line. We propose a system using a spectral camera which can be viewed as a line scan camera composed of an array of point spectrometers. Three types of lighting system that exhibit different illumination spectrums are devised together with a calibration method of the proposed spectral camera system. To visualize the defect areas, various processing algorithms to identify and to enhance the small differences in spectrum between defective and normal areas are developed. Experiments shows 85% successful visualization. of real samples using the proposed system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1634-1637
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• 2003

Any given object on the motor-driven turntable is pictured from 8 to 72 different views with a digital camera. 3D shape reconstruction is performed with the integrated software called by Scanware from these multiple digital photographs. There are several steps such as configuration, calibration, capturing, segmentation, shape creation, texturing and merging process during the shape reconstruction process. 3D geometry data can be exported to cad data such as Autocad input file. Also 3D image model is generated from 3D geometry and texture data, and is used to advertise the model in the internet environment. Consumers can see the object realistically from wanted views by rotating or zooming in the internet browsers with Scanbull spx plug-in. The spx format allows a compact saving of 3D objects to handle or download. There are many types of scan equipments such as laser scanners and photogrammetric scanners. Line or point scan methods by laser can generate precise 3D geometry but cannot obtain color textures in general. Reversely, 3D image modeling with photogrammetry can generate not only geometries but also textures from associated polygons. We got various 3D image models and introduced the process of getting 3D image model of an internet-connected watchdog robot.