• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.83-90
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• 1999

In this paper, we studied resolution to the FBP and BFP image reconstruction algorithms for ultrasonic diffraction tomography. In order to analyze the resolution to the tomographic images which can be reconstructed from the modified FBP image reconstruction algorithm by using fixed coordinate system and BFP image reconstruction algorithm which is suitable for plane structure object, we derived ambiguity functions to these algorithms and then analyzed lateral and depth resolution through simulation respectively. Simulation results show that the lateral and depth resolution to the FBP image reconstruction algorithm and the BFP image reconstruction algorithm was determined 0.27 λ, 0.70 λ and 0.39 λ, 0.98 λ at the 3dB respectively. These results imply that modified FBP and BFP image reconstruction algorithms for diffraction tomography is useful in the tomographic image reconstruction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.139-143
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• 2023

In this paper, compared to the RT algorithm that constitutes CT images, the TPSM algorithm available in the conical CB-CT system was applied to enable 3D CT image configuration faster than the existing RT, and the image speeds of the two algorithms were compared and analyzed. To this end, the TPSM algorithm available in the conical CB-CT system was applied to enable real-time processing in 3D CT image composition. As a result of the experiment, it was found that the cross-sectional image constructed using TPSM decreases the quality of the image slightly by empty pixels as the distance from the center point increases, but in the case of TPSM rotation-based methods, the image composition speed is far superior to that of the RT algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.299-307
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• 2016

While segmenting "complex" images (with multiple objects, many details, etc.) we experienced a need to explore new ways for time-efficient and meaningful image segmentation. In this paper we propose a new technique for image segmentation which has only one variable for controlling the expected number of segments. The algorithm focuses on the treatment of pixels in transition zones between various label distributions. Results of the proposed algorithm (e.g. on the Berkeley image segmentation dataset) are comparable to those of GMM or HMM-EM segmentation, but are achieved with significantly reduced computation time.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1292-1304
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• 2012

Recently, digital images are extremely forged by editors or advertisers. Also, amateurs can modify images throughout easy editing programs. In this study, we propose identification and analytical methods for the modified images to figure out those problems. In modified image analysis, we classify two parts; a filtering change and a geometric change. Those changes have an algorithm based on interpolation so that we propose the algorithm which is able to analyze a trace on a modified area. With this algorithm, we implement a detection map of interpolation using minimum filter, laplacian algorithm, and maximum filter. We apply the proposed algorithm to modified image and are able to analyze its modified trace using the detection map.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.78-88
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• 1995

For producing iron or steel products with good quality, the concentration of the material components should be analyzed quickly with high relability using XRF(Fluorescent X-Ray Spectrometer). Since the analysis results are much dependent upon the surface con- dition, the samples have to be prepared to have good test condition. This study presents an image processing system for inspecting the surface condition of the iron test sample. In order to use thd computer vision system, we need to develop a lighting device and image processing algorithm. For the adequate lighting device of inspection system, the indirect lighting device is contrived to cut the external light and provide uniform, stable and cold light. The image processing algorithm is aimed to reduce inspection time and to get similar analyzing results to those of the experienced operators. At first, the image processing algorithm checks whether the surface of the iron sample is ground well or not. Then, the defects; hole or dig are conted and surface condition is evaluated. In addition, the algorithm gives the reliability of the analyzing results in order to help operator's decision.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.1
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• pp.13-23
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• 2015

Recently, a few image-processing based mobile urine testers have actively been studied since the urine-analysis result can be available to the user in real time immediately after the test is done. However, the accuracy of test result can be severely degraded due to variable illumination environments and a variety of manners to capture the image with a camera embedded in the smartphone according to different users. This paper proposes the Check4Urine system, a novel smartphone-based portable urine-analysis tester and provides three techniques to improve such a performance degradation problem robust to various test environments and disturbances, which are the compensation algorithm to correct the varying illumination effect, an urine strip detection algorithm robust to edge loss of the object image, and the color decision algorithm based on the pre-processed reference table. Experimental results show that the proposed Check4Urine system increases the accuracy of urine-analysis by 20-50% at various test conditions, compared with the existing image-processing based mobile urine tester.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.129-132
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• 2000

In this paper, we deal with content based searching algorithm for brand image using GHA(Generalized Hebbian Algorithm). GHA is a part of PCA(Principal Component Analysis), that has single-layer perceptron operates and self-organizing performances. We used this algorithm for feature extracts of brand images, and our simulations verify the high performance than present text based methods.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.151-159
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• 2021

To derive grid lines for analyzing a table layout, line image enhancement techniques are studying such as various filtering or morphology methods. In spite of line image enhancement, it is still hard to extract line components and to express table cell's layout logically in which the cutting points are exist on the line or the tables are skewing . In this paper, we proposed a line tracking algorithm to extract line components under the cutting points on the line or the skewing lines. The table document layout analysis algorithm is prepared by searching grid-lines, line crossing points and gird-cell using line tracking algorithm. Simulation results show that the proposed method derive 96.4% table document analysis result with average 0.41sec processing times.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.256-261
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• 2013

In the steel manufacturing area, researches for defect inspection receive a big attention for quality control. This paper proposes an algorithm to detect a scratch defect on steel billets. This algorithm takes ROIs (Regions of Interest), and extracts 11 features which represent properties of defect on a ROI. SVM (Support Vector Machine) is used to classify defect and normal ROIs. The algorithm classifies a frame image of a Billet as a defect image if there is one or more defect ROIs. In the experiments, the proposed algorithm had reliable classifying accuracy.

• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.138-145
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• 2010

An on-line algorithm that discriminates brown rice kernels on their echelon feeder using color image processing is presented for quality inspection. A rapid color image segmentation algorithm based on Bayesian clustering method was developed by means of the look-up table which was made from the significant clusters selected by experts. A robust estimation method was presented to improve the stability of color clusters. Discriminant analysis of color distributions was employed to distinguish nine types of brown rice kernels. Discrimination accuracies of the on-line discrimination algorithm were ranged from 72% to 85% for the sound, cracked, green-transparent and green-opaque, greater than 93% for colored, red, and unhulled, about 92% for white-opaque and 67% for chalky, respectively.