• Korean Journal of Radiology
• /
• v.23 no.4
• /
• pp.402-412
• /
• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.282-285
• /
• 2006

This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.1
• /
• pp.31-40
• /
• 2024

Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.2
• /
• pp.260-267
• /
• 2011

This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.

• KIISE Transactions on Computing Practices
• /
• v.23 no.3
• /
• pp.141-147
• /
• 2017

Recently there has been an increasing demand for developing a domestic software (S/W) for infrared signature generation to prevent technology leakage and match the domestic operating environment. In this study, we developed a S/W for infrared signature generation and presented its structures and functions for creating and analyzing the IR images of designated spectral bands. The proposed S/W generates IR images of an object through calculations of surface temperatures and IR signals including the self-emitted, surface reflected and path dependent radiances. Moreover, the proposed S/W includes the features of infrared threat analyses from the generated IR images including the infrared contrast radiant intensity (CRI), detection ranges or detection probability analyses, unlike the imported, commercial infrared signature generation S/W.

• Elastomers and Composites
• /
• v.54 no.2
• /
• pp.110-117
• /
• 2019

The characterization of the ozone oxidation for raw natural rubber (NR) was investigated under controlled conditions through image and fourier transform infrared (FT-IR) analysis. The ozone oxidation was performed on a transparent thin film of raw NR coated on a KBr window in a dark chamber at $40^{\circ}C$ under low humidity conditions to completely exclude thermal, moisture, or light oxidation. The ozone concentration was set at 40 parts per hundred million (pphm). Before or after exposure to ozone, the image of the thin film for raw NR was observed at a right or tilted angle. FT-IR absorption spectra were measured in the transmission mode according to ozone exposure time. The ozone oxidation of NR was determined by the changes in the absorption peaks at 1736, 1715, 1697, and $833cm^{-1}$, which were assigned to an aldehyde group (-CHO), a ketone group (-COR), an inter-hydrogen bond between carbonyl group (-C=O) from an aldehyde or a ketone and an amide group (-CONH-) of protein, and a cis-methine group ($is-CCH_3=CH-$, respectively. During ozone exposure period, the results indicated that the formation of the carbonyl group of aldehyde or ketone was directly related to the decrement of the double bond of cis-1,4-polyisoprene. Only carbonyl compounds such as aldehydes or ketones seemed to be formed through chain scission by ozone. Long thin cracks with one orientation at regular intervals, which resulted in consecutive chain scission, were observed by image analysis. Therefore, one possible two-step mechanism for the formation of aldehyde and ketone was suggested.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.3
• /
• pp.13-20
• /
• 2009

Techniques for change detection using satellite images enable efficient detection of natural and artificial changes in use of land through multi-phase images. As for change detection, different results are made based on methods of calibration of satellite images, types of input data, and techniques in change analysis. Thus, an analytic technique that is appropriate to objectives of a study shall be applied as results are different based on diverse conditions even when an identical satellite and an identical image are used for change detection. In this study, Normalized Difference Vegetation Index (NDVI) and Principal Component Analysis (PCA) were conducted after geometric calibration of satellite images which went through absolute and relative radiometric calibrations and change detection analysis was conducted using Image Difference (ID) and Image Rationing (IR). As a result, ID-NDVI showed excellent accuracy in change detection related to vegetation. ID-PCA showed 90% of accuracy in all areas. IR-NDVI had 90% of accuracy while it was 70% and below as for paddies and dry fields${\rightarrow}$grassland. IR-PCA had excellent change detection over all areas.

• Elastomers and Composites
• /
• v.51 no.1
• /
• pp.1-9
• /
• 2016

Characterization of the UV oxidation for raw natural rubber (NR) was investigated in controlled conditions through image and FT-IR analysis. The UV oxidation was performed on a thin film of natural rubber coated on a KBr window at 254 nm and room temperature to exclude the thermal oxidation. Before or after exposure to UV light, image of the NR thin film was observed at a right or tilted angle. FT-IR absorption spectra were measured in transmission mode with the UV irradiation time. The UV oxidation of NR was examined by the changes of absorption peaks at 3425, 1717, 1084, 1477, 1377, and $833cm^{-1}$ which were assigned to hydroxyl group (-OH), carbonyl group (-C=O), carbon-oxygen bond (-C-O), methylene group $(-CH_2-)$, methyl group $(-CH_3)$, and cis-methine group $(cis-CCH_3=CH-)$, respectively. During the initial exposure period, the results indicated that the appearance of carbonyl group was directly related to the reduction of cis-methine group containing carbon-carbon double bond (-C=C-). Most of aldehydes or ketones from carbon-carbon double bonds were formed very fast by chain scission. A lot of long wide cracks with one orientation at regular intervals which resulted in consecutive chain scission were observed by image analysis. During all exposure periods, on the other hand, it was considered that the continuous increment of hydroxyl and carbonyl group was closely related to the decrement of methylene and methyl group in the allylic position. Therefore, two possible mechanisms for the UV oxidation of NR were suggested.

• Korean Journal of Remote Sensing
• /
• v.6 no.1
• /
• pp.11-24
• /
• 1990

This is the study about the meteorological satellite cloud image classification by objective methods. For objective cloud classification, linear discriminant analysis was tried. In the linear discriminant analysis 27 cloud characteristic parameters were retrieved from GMS infrared image data. And, linear cloud classification model was developed from major parameters and cloud type coefficients. The model was applied to GMS IR image for weather forecasting operation and cloud image was classified into 5 types such as Sc, Cu, CiT, CiM and Cb. The classification results were reasonably compared with real image.

• Journal of Internet Computing and Services
• /
• v.14 no.2
• /
• pp.45-51
• /
• 2013

In this paper, the combination of ultraviolet and infrared sensors based design for flame signal detection algorithms was proposed with the application of light-wavelength from burning. And, the performance result of image detection was compared by an ultraviolet sensor, an infrared sensor, and the proposed dual-mode sensors(combination of ultraviolet and infrared sensors).