• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.311-314
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• 1995

This paper presents a method for measuring tool wear parameters based on two dimensional image information. The tool wear images were obtained from an ITV camera with magnifying and lighting devices, and were analyzed using image processing techniques such as thresholding, noise filtering and boundary tracing. Thresholding was used to transform the captured gray scale image into a binary image for rapid sequential image processing. The threshold level was determined using a novel technique in which the brightness histograms of two concentric windows containing the tool wear image were compared. The use of noise filtering and boundary tracing to reduce the measuring errors was explored. Performance tests of the measurement precision and processing speed revealed that the direct method was highly effective in intermittent tool wear monitoring.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.192-198
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• 2008

Purpose: The scan time reduction helps to yield more accurate results and induce the minimization of patient's motion. Also we can expect that satisfaction of examination will increase. Nowdays medical equipment companies have developed various programs to reduce scan time. We used Onco. Flash (Pixon method, SIEMENS) that is an image processing technique gated cardiac blood pool scan and going to evaluate its clinical usefullness. Materials and Method: We analyzed the 50 patients who were examined by gated blood pool scan in nuclear medicine department of Asan Mediacal Center from June $20^{th}$ 2008 to August $14^{th}$ 2008. We acquired the Full-time (6000 Kcounts) and Half-time (3000 Kcounts) LAO image in same position. And we acquired LVEF values ten times from Full-time, Half-time images acquired by the image processing technique and analyzed its mean and standard deviation values. To estimate LVEF in same conditions, we set automatic location of the LV ROI and background ROI based on same X and Y-axis. Also we performed blinding tests to physician. Results: After making a quantitative analysis of the 50 patients EF values, each mean${\pm}$standard deviation is shown at Full-time image $68.12{\pm}7.84%$, Half- time (acquired by imaging processing technique) $68.49{\pm}8.73%$. In the 95% confidence limit, there was no statistically significant difference (p>0.05). After blinding test with a physician for making a qualitative analysis, there was no difference between Full-time image and Half-time image acquired by the image processing technique for observing LV myocardial wall motion. Conclusion: Gated cardiac blood pool scan has been reported its relatively exact EF measured results than ultrasound or CT. But gated cardiac blood pool scan takes relatively longer time than other exams and now it needs to improve time competitive power. If we adapt Half-time technique to gated cardiac blood pool scintigraphy based on this study, we expect to reduce possible artifacts and improve accessibility as well as flexibility to exam. Also we expect patient's satisfaction.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.98-103
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• 2010

In this paper, imaging processing study obtained from CCD image and thermography image was performed in order to treat easily thermographic data without any risks of personnels who conduct the condition monitoring for the abnormal or failure status occurrable in industrial power plants. This imaging processing is also applicable to the predictive maintenance. For confirming the broad monitoring, a methodology producting single image from the panorama technique was developed no matter how many cameras are employed, including fusion method for discrete configuration for the target. As results, image fusion from quick realtime processing was obtained and it was possible to save time to track the location monitoring in matching the images between CCTV and thermography.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.811-815
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• 1990

This paper describes the method on image acquisition and image processing in the turning process. The formation of discontinuous chips during high-speed oblique cutting without lubricant was observed by means of video camera recorder and stroboscope. The image processing technique for chip flow is described and the results are presented for variable feeds. It is concluded that experimental values of chip flow angle are similar to theoretical values of Stabler's rule.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.72-74
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• 1997

We have developed a 3-D image processing and display technique that include image resampling, modification of MIP, and fusion of MIP image and volumetric rendered image. This technique facilitates the visualization of the three-dimensional spatial relationship between vasculature and surrounding organs by overlapping the MIP image on the volumetric rendered image of the organ. We applied this technique to a MR brain image data to produce an MRI angiogram that is overlapped with 3-D volume rendered image of brain. MIP technique was used to visualize the vasculature of brain, and volume rendering was used to visualize the other structures of brain. The two images are fused after adjustment of contrast and brightness levels of each image in such a way that both the vasculature and brain structure are well visualized either by selecting the maximum value of each image or by assigning different color table to each image. The resultant image with this technique visualizes both the brain structure and vasculature simultaneously, allowing the physicians to inspect their relationship more easily. The presented technique will be useful for surgical planning for neurosurgery.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.405-408
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• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1058-1070
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• 2014

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.160-165
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• 1998

Current discriminating technique of rice variety is known to be not objective till this time because of depending on naked eye of well trained inspector. DNA finger print method based on genetic character of rice has been indicated inappropriate for on-site application, because the method need much labor and skilled expert. The purpose of this study was to develops the identification technique of polished rice varieties using CCD camera images. To minimize the noise of the captured image, thresholding and median filtering were carried out, and edge was extracted from the image data. Image data after pretreatment of normalize and FFT(fast fourier transform) were used for library model and feedforward backpropagation neural network model. Image processing technique using CCD camera could discriminate the variety of rice with high accuracy in case of quite different rice of shape, but the accuracy was reached at 85% in the similar shape of rice.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.227-235
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• 2003

We propose an algorithm for the automatic measurement of concentricity and roundness using image processing technique. The proposed measuring method consists of the preprocessing process and the measuring process. In the measuring process, two types of concentricity measurement algorithm and one type of roundness measurement algorithm are proposed. We could measure the concentricity and roundness using input image from CCD camera, without using special measurement equipment. From the experimental results, we could find that the required measurement accuracy specification is sufficiently satisfied using our proposed method.