• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.228-230
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• 2002

The relative electron density resolution was discussed by the noise power spectrum (NPS) in the heavy ion CT image. The heavy ion beam $\^$12/C accelerated up to 400MeV/u by RIMAC was used in this study. The two-dimensional (2-D) NPS in the CT image was obtained from the one-dimensional (1-D) NPS of the measured residual range distribution of water phantom for single projection, and the noise variance in the CT image was calculated from 2-D NPS. The technique used in the reconstruction was the filtered back-projection method with Shepp-Logan filter. The calculated value suggests the result of our previous works using the density resolution phantom, assuming that the relative electron density resolution is twice the standard deviation. Therefore, the estimation of the noise in CT images by 2-D NPS obtained the measured residual range distribution is the useful method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Korean Journal of Digital Imaging in Medicine
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• v.16 no.2
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• pp.1-7
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• 2014

This study is to increase the accuracy of the diagnosis of benign prostatic hyperplasia by presenting a method that can accurately measure the residual urine amount of the bladder by using an ultrasound image. Agar powder, Propanol and distilled water were used as materials for making a phantom. In order to measure the volume, a $10m{\ell}$ cylinder, syringe and beaker were used. The image was obtained by scanning phantoms produced into six shapes. Each constant value was obtained by using the expression designed to measure the residual urine amount of the bladder and was compared and analyzed. The measuring method of Bladder volume was presented and a constant value for each shape was obtained and five observers measured it five times. According to the results of clinical application, the errors of Ellipse-beanbag, Shield-shield were 11.0%, 18.2%, respectively. Constant values depending on the shape of each phantom were presented in order to accurately measure the volume of the bladder in measuring the amount of residual urine for the diagnosis of benign prostatic hyperplasia. The accuracy of the volume using this was verified statistically(p > 0.05). Therefore, it is considered to be useful in diagnosing benign prostatic hyperplasia by using the ultrasound imaging measuring method presented.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.1
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• pp.30-36
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• 2008

Recently, ere are many researches to improve the quality of e medical service such as Point of care (POC). To improve the quality of the medical service, not only good medical device but also more man power is required. Especially, the number of nurses are very few in Korea that is almost the lowest rank compared to OECD countries. If the simple repetition works of the nurse could be removed, it is possible to use the skillful nurse for other works and provide better quality services. There are many simple repetition works which the nurses have to do, such as replacing the ringer's solution. To replace the ringer's solution automatically, it is necessary to detect residual quantity of the ringer's solution. In this paper, image processing is used to detect the residual quantity of ringer's solution, and modified self quotient image (SQI) algorithm is used to strong background lights. After modified SQI algorithm, the simple histogram accumulation is done to find the residual quantity of the ringer's solution. The implemented algorithm could be use to replace the ringer's solution automatically or alarm to the nurses to replace the solution.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.483-490
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• 2022

Malaria is a disease caused by a parasite and it is prevalent in all over the world. The usual method used to recognize malaria cells is a thick and thin blood smears examination methods, but this method requires a lot of manual calculation, so the efficiency and accuracy are very low as well as the lack of pathologists in impoverished country has led to high malaria mortality rates. In this paper, a malaria cell image recognition model using transfer learning is proposed, which consists in the feature extractor, the residual structure and the fully connected layers. When the pre-training parameters of the VGG-19 model are imported to the proposed model, the parameters of some convolutional layers model are frozen and the fine-tuning method is used to fit the data for the model. Also we implement another malaria cell recognition model without residual structure to compare with the proposed model. The simulation results shows that the model using the residual structure gets better performance than the other model without residual structure and the proposed model has the best accuracy of 97.33% compared to other recent papers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.47-52
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• 2016

The used digital images in the smart device and small displayer has been a downscaled image. In this paper, the detection of the downscaling image forgery is proposed using the feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value's gradients of the image. These coefficients as the feature vectors are used in the learning of a SVM (Support Vector Machine) classification for the downscaling image forgery detector. On the performance of the proposed algorithm, it is excellent at the downscaling 90% image forgery compare to MFR (Median Filter Residual) scheme that had the same 10-Dim. feature vectors and 686-Dim. SPAM (Subtractive Pixel Adjacency Matrix) scheme. In averaging filtering ($3{\times}3$) and median filtering ($3{\times}3$) images, it has a higher detection ratio. Especially, the measured performances of all items in averaging and median filtering ($3{\times}3$), AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Journal of Welding and Joining
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• v.22 no.3
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• pp.45-49
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• 2004

Generally, it is used the compensation spring to compensate the inaccuracy of screen image induced by thermal deformation in CRT monitor. Its mechanism is hi-metallic system made of heterogeneous metals and these springs are bonded by laser welding. But laser welding induces a non-uniform temperature distribution, and residual stress is yielded locally by these temperature deviation. Therefore, this study measures the curvature constant to assess functions of the compensation spring of shadow mask with respect to increment temperature and estimates the effect of residual stress on the performance of tri-metal used to compensation spring.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.3
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• pp.105-121
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• 1994

In this paper, we proposed the two-parameter model for predicting the residual strength in CFRP laminated composites subjected to high velocity impact and developed and formulated it based upon Cparino's by using the ratio of impact and the normalized residual strength. Critical indentation was obtained by the statical indentation tests. Impact tests were carried out through air-gun type impact equipment with the velocities varied 30-100m/sec. Projectiles were steel balls with 5 and 7mm in diameter. Test material was carbon/epoxy. The specimens were composed of [ .+-. 45 .deg. /0 .deg. /90 .deg. ]$\_$2/ and [ .+-. 45 .deg. ]$\_$4/stacking sequences and had 0.75$\^$T/*0.26$\^$W/*100$\^$L/(mm) dimension. Results from the proposed model were in good agreement with the test data. And failure mechanism due to high velocity impact is given here to examine the initation and deveolpment of damage by fractography and ultrasonic image system. The effects of the 0 .deg. -direction ply position and the amount to damage area on the residual strength are considered here.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.213-218
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• 2013

Although infrared focal plane array (IRFPA) detectors have been commonly used, non-uniformity correction (NUC) remains an important problem in the infrared imaging realm. Non-uniformity severely degrades image quality and affects radiometric accuracy in infrared imaging applications. Residual non-uniformity (RNU) significantly affects the detection range of infrared surveillance and reconnaissance systems. More effort should be exerted to improve IRFPA uniformity. A novel NUC method that considers the surrounding temperature variation compensation is proposed based on the binary nonlinear non-uniformity theory model. The implementing procedure is described in detail. This approach simultaneously corrects response nonlinearity and compensates for the influence of surrounding temperature shift. Both qualitative evaluation and quantitative test comparison are performed among several correction technologies. The experimental result shows that the residual non-uniformity, which is corrected by the proposed method, is steady at approximately 0.02 percentage points within the target temperature range of 283 K to 373 K. Real-time imaging shows that the proposed method improves image quality better than traditional techniques.