• Journal of Biosystems Engineering
• /
• v.28 no.5
• /
• pp.439-448
• /
• 2003

An image processing algorithm was developed for a robot system which was used in gene study. The robot system achieved a job of colony picking. The colony included DNA of an organism. The robot picked up the colony in petri-dish, which included the cultivated colony in medium, by a picking pin, and moved the colony to wellplates. The vision system consisted of an image acquisition system which acquired the image information of colony, an illumination device which irradiated the object once when it got the image of it, a computer and so on. The image processing algorithm distinguished the colony and detected colony positions. Performance test of the developed algorithm showed that the distinguishing success rate of colony and detecting success rate of colony positions were over 96%.

• International Journal of Contents
• /
• v.2 no.1
• /
• pp.5-8
• /
• 2006

This paper describes a new mechanism of detecting object of interest from a noisy image, without using any a-priori knowledge about the target. It employs a parallel set of filters inspired upon biological findings of mammalian vision. In our proposed system, several basic features are extracted directly from original input visual stimuli, and these features are integrated based on their local competitive relations and statistical information. Through integration process, unnecessary features for detecting the target are spontaneously decreased, while useful features are enhanced. Experiments have been performed on a set of computer generated and real images corrupted with noise.

• Proceedings of the IEEK Conference
• /
• 2002.06e
• /
• pp.211-214
• /
• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• Journal of Animal Environmental Science
• /
• v.7 no.3
• /
• pp.177-182
• /
• 2001

This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.

• Journal of Internet Computing and Services
• /
• v.13 no.3
• /
• pp.17-22
• /
• 2012

In this paper, a photoelectric image detection system is proposed using an APD(Avalanche Photodiode) sensor, a LED illuminator, and fiberoptic waveguides. This proposed pinhole detection system can detect the pinholes of 100 micron with the speed rate of 1,000mpm(meter per minute). And detecting performance of image system is improved by the SQL based DB analysis of classifying pinhole's detected location and size using image detection algorithms.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2319-2322
• /
• 2003

We propose ROI(region of interest) image coding application to still image using PSBS(partial significant bitplane shift)method combined with human face region detecting system. PSBS is an encoding algorithm for ROI image coding in JPEG2000, and takes advantages of both generic scaling based method and maximum shift method defined in JPEG2000. The Powerful advantages of PSBS are able to adjusting image quality in ROI and background flexibly, and support arbitrarily shaped ROI coding without coding the shape. In this letter, we show how to compress an image for human face region using PSBS method combined with human face region detecting system, and propose its application.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.32A no.4
• /
• pp.65-74
• /
• 1995

In this paper, we propose a new technique to segment the moving target image from the natural background. This system as based on the optical BPEJTC for both detecting the moving target and automatically extracting the target image from the background by gradually eliminating the background image through the repeated correlation processes. Some computer simulation and experimental results show that the proposed system can effectively segment the moving car image from the fixed background, and that this system can be used for a fast moving target segmentation system.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1130-1133
• /
• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Korean Journal of Digital Imaging in Medicine
• /
• v.16 no.2
• /
• pp.25-29
• /
• 2014

The full-field digital mammography (FFDM), which has been known as a digital breast imaging system, carries out more outstanding performance than the screen-film mammography in overall image quality, skin & nipple, description of pectoral muscle and expression of micro-calcification. Thus, in this thesis, I perform experiments for both the enhancement of image quality and accurate estimation of the result in question, when detecting the very tiny-sized lesions in mammography. The image of digital breast X-rays is the important diagnostic tool for detecting early breast cancer and micro calcification lesion. The experiment of how much compression rate has an effect on the result of diagnosis in the case of microcalcification lesion, with JPEG2000 40:1 compression and over 50% enlargement led to obscure or definitely unacceptable diagnostic results is performed. And in another study of assessment of PSNR degree. I recognized the importance of standardized management system in mammography, where not to mention the accurate reading of the image has the most crucial role in diagnosis

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.12
• /
• pp.1813-1819
• /
• 2013

Existing level crossing obstacle detecting system was installed using a laser beam. Level crossing obstacle detecting system using a laser beam that has been a problem in relation to safety and maintainability failure according to weather conditions. We proposed laser radar level crossing obstacle detecting system as a way to overcome problem, and we developed an algorithm for this. Level crossing obstacle detecting system using a laser radar sensor algorithm is robust to external environment and a shadow zone does not exist. Sensor part of the laser radar level crossing obstacle detecting system of these is made up by the image processing unit and laser radar sensor, it operations by receiving train entering information from the control unit. In this paper, we proposed a detecting algorithm with calculation of the size of the laser radar sensor. Based on this, we were performance test on the basis of the scenario by making a prototype. In the future, laser radar level crossing obstacle detecting system to ensure the safety and reliability through the field test.