• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.206-213
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• 1996

Third order correlation funciton is to be advantageous to detect unique features embedded in various random signals that are undetectable with second order correlation or power spectrum. In this paper, we will introduce optical modulator which consists of a laser light source, 2-dimensional ultrasonic diffractor cell with signal controlling circuitry, and a CCD camera connected to personal computer for image processing. With this modulator, the third order correlaiton pattern of signal can be immediately obtained at the camera due to parallel nature of optical computing.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.53-54
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• 2007

Charged particle type display using particles which have opposite charge and color is based on effect of reversible optical property due to electric field. we designed mask pattern for fabrication of the charged particle type display based on glass substrate and investigated cell gap dependent of driving voltage and selectively driving method. the panel driven by our selectively driving method, we could obtain image which had vary little crosstalk caused by electrical interference and conform the last image maintained by memory effect without additional voltage.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.83-90
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• 2011

In cell biology area, microscopy enables detecting objects inside cells that are stained or fluorescently tagged. It is disadvantageous for observing these objects because of the noisy characteristics of their environmental surrounding. In this paper, a framework is proposed to increase the throughput and reliability for analysis of these images. First, we apply adaptive beamlet transform to extract edges meaningfully followed by orientation, location, and length in different scales. Then, a post-process is implemented to extend and map them onto original image. Our proposed scheme is compared with Canny edge detector and conventional beamlet transform from four evaluation aspects. It produces better results when experiments are conducted on real images. Much better results for observing internal parts make this framework competitive for analysis of cell images.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.373-381
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• 2021

In this paper, we propose a classification model based on convolutional neural network(CNN) for predicting 2-year recurrence in non-small cell lung cancer(NSCLC) patients using preoperative chest CT images. Based on the region of interest(ROI) defined as the tumor internal and external area, the input images consist of an intratumoral patch, a peritumoral patch and a peritumoral texture patch focusing on the texture information of the peritumoral patch. Each patch is trained through AlexNet pretrained on ImageNet to explore the usefulness and performance of various patches. Additionally, ensemble learning of network trained with each patch analyzes the performance of different patch combination. Compared with all results, the ensemble model with intratumoral and peritumoral patches achieved the best performance (ACC=98.28%, Sensitivity=100%, NPV=100%).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.1003-1006
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• 2012

The image correction algorithm and system design for CMOS sensor to enhance the image resolution is presented in this paper. The proposed algorithm finds out the image cell from the sensor and process them by the limited memory configuration. The evaluation of the method is done by the designed hardware system. The experimental results are capable of improving contrast per channel and of sensing equalized image quality on an edge of image.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1640-1643
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• 2002

Image sticking, the phenomenon that the previously displayed pattern still remains after the image is changed into different image, is one of the most serious problem in realizing high picture quality. In this paper, we tried characterizing this undesirable feature in terms of the luminance and the intial firing voltage at ramp up time in reset period. It was found that the cell located at the boundary of previous image pattern show low firing voltage and high background luminance. And the results show that the degree of the image sticking is severely affected by discharge duration and the length of the sustain period.

• Fisheries and Aquatic Sciences
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• v.4 no.1
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• pp.1-9
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• 2001

This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.69-79
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• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.160-164
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• 2011

Squamous cell carcinoma of the pancreas is a rare, uncommon tumor that is characterized by squamous metaplasia of the ductal columnar cells. We report the image findings of a rare case of the pancreatic squamous cell carcinoma associated with chronic pancreatitis.