• Progress in Medical Physics
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• v.24 no.3
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• pp.162-170
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• 2013

Dedicated single-photon emission computed tomography (SPECT) systems based on pixelated semiconductors are being developed for studying small animal models of human disease. To clarify the possibility of using a SPECT system with CdTe for a high resolution low-dose small animal imaging, we compared the quality of reconstructed images from pixelated CdTe detector to those from a small SPECT system with NaI(Tl). The CdTe detector was $44.8{\times}44.8$ mm and the pixels were $0.35{\times}0.35{\times}5$ mm. The intrinsic resolution of the detector was 0.35 mm, which is equal to the pixel size. GATE simulations were performed to assess the image quality of both SPECT systems. The spatial resolutions and sensitivities for both systems were evaluated using a 10 MBq $^{99m}Tc$ point source. The quantitative comparison with different injected dose was performed using a voxelized MOBY phantom, and the absorbed doses for each organ were evaluated. The spatial resolution of the SPECT with NaI(Tl) was about 1.54 mm FWHM, while that of the SPECT with a CdTe detector was about 1.32 mm FWHM at 30 mm. The sensitivity of NaI(Tl) based SPECT was 83 cps/MBq, while that of the CdTe detector based SPECT was 116 cps/MBq at 30 mm. The image statistics were evaluated by calculating the CNR of the image from both systems. When the injected activity for the striatum in the mouse brain was 160 Bq/voxel, the CNR of CdTe based SPECT was 2.30 while that of NaI(Tl) based SPECT was 1.85. The CNR of SPECT with CdTe was overall higher than that of the NaI(Tl) based SPECT. In addition, the absorbed dose was higher from SPECT with CdTe than those from NaI(Tl) based SPECT to acquire the same quantitative values. Our simulation results indicated that the SPECT with CdTe detector showed overall high performance compared to the SPECT with NaI(Tl). Even though the validation study is needed, the SPECT system with CdTe detector appeared to be feasible for high resolution low-dose small animal imaging.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.1-14
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• 2000

The rosette-scan seeker, mounted on the infrared guided missile, is a device that tracks the target It can acquire the 2D image of the target by scanning a space about target in rosette pattern with a single detector Since the detected image is changed according to the position of the object in the field of view and the number of the object is not fixed, the unsupervised methods are employed in clustering it The conventional ISODATA method clusters the objects by using the distance between the seed points and pixels So, the clustering result varies in accordance with the shape of the object or the values of the merging and splitting parameters In this paper, we propose an Array Linkage Clustering Algorithm (ALCA) as a new clustering algorithm improving the conventional method The ALCA has no need for the initial seed points and the merging and splitting parameters since it clusters the object using the connectivity of the array number of the memory stored the pixel Therefore, the ALCA can cluster the object regardless of its shape With the clustering results using the conventional method and the proposed one, we confirm that our method is better than the conventional one in terms of the clustering performance We simulate the rosette scanning infrared seeker (RSIS) using the proposed ALCA as an infrared counter countermeasure The simulation results show that the RSIS using our method is better than the conventional one in terms of the tracking performance.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1061-1073
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• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Journal of the Korean Vacuum Society
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• v.20 no.1
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• pp.22-29
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• 2011

An infrared thermographic imaging module of [$320{\times}256$] focal-plane array (FPA) based on [InAs/GaSb] strained-layer superlattice (SLS) was fabricated, and its images were demonstrated. The p-i-n device consisted of an active layer (i) of 300-period [13/7]-ML [InAs/GaSb]-SLS and a pair of p/n-electrodes of (60/115)-period [InAs:(Be/Si)/GaSb]-SLS. FTIR photoresponse spectra taken from a test device revealed that the peak wavelength (${\lambda}_p$) and the cutoff wavelength (${\lambda}_{co}$) were approximately $3.1/2.7{\mu}m$ and $3.8{\mu}m$, respectively, and it was confirmed that the device was operated up to a temperature of 180 K. The $30/24-{\mu}m$ design rule was applied to single pixel pitch/mesa, and a standard photolithography was introduced for [$320{\times}256$]-FPA fabrication. An FPA-ROIC thermographic module was accomplished by using a $18/10-{\mu}m$ In-bump/UBM process and a flip-chip bonding technique, and the thermographic image was demonstrated by utilizing a mid-infrared camera and an image processor.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.149-158
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• 2017

Fine temporal and spatial resolution of image data are necessary to monitor the phenology of vegetation. However, there is no single sensor provides fine temporal and spatial resolution. For solve this limitation, researches on spatiotemporal data fusion methods are being conducted. Among them, FSDAF (Flexible spatiotemporal data fusion) can fuse each band in high accuracy.In thisstudy, we applied MODIS NDVI and Landsat NDVI to enhance time resolution of NDVI based on FSDAF algorithm. Then we proposed the possibility of utilization in vegetation phenology monitoring. As a result of FSDAF method, the predicted NDVI from January to December well reflect the seasonal characteristics of broadleaf forest, evergreen forest and farmland. The RMSE values between predicted NDVI and actual NDVI (Landsat NDVI) of August and October were 0.049 and 0.085, and the correlation coefficients were 0.765 and 0.642 respectively. Spatiotemporal data fusion method is a pixel-based fusion technique that can be applied to variousspatial resolution images, and expected to be applied to various vegetation-related studies.

• Journal of Periodontal and Implant Science
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• v.31 no.1
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• pp.257-269
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• 2001

Removal of subgingival calculus is essential for the success in periodontal treatment. Subgingival instrumentation is used for the removal of all bacterial plaque and calculus. In this study, Gracey curet and Ultrasonic curet were used on single rooted teeth to conduct subgingval scaling and root planning. The remaining amount of calculus was evaluated according to type of instrument, depth of pocket, and tooth surface. 24 teeth were extracted from 14 patients being treated at department Periodontology Seoul Advantist dental hospital were used. Total 96 area(4 surface per teeth) were evaluated. 12 teeth treated with Gracey curet were used as the control group and the other 12 teeth treated with Ultrasonic curet were examined for experimental group. The 4 surface of the teeth(buccal, mesial, lingual or palatal, distal) were observed through the stereomicroscope and the images of the surface were captured and saved in CCD. The images were displayed on the monitor and the amount of calculus remained was evaluated by overlapping $10{\times}10$ grid pixel screen produced by Microsoft power point. The results evaluated were as follows 1. There was no statistically significant difference in residual calculus and tooth position following scaling and root planning of all group, but statistically significant correlation with residual calculus, probing depth, instruments and tooth surface. 2. There was statistically significant correlation between residual calculus and probing depth, but no statistically significant difference in residual calculus, tooth surface and tooth position on experimental(Ultrasonic curet) group. 3. There was no statistically significant difference in residual calculus according to the pre-treatment pocket depth and tooth position, but statistically significant correlation with tooth surface. The amount of residual calculus increase with mesial, distal, buccal and lingual(or palatal) surface on control(Gracey curet) group. 4. The Gracey showed better results than ultrasonic curet in mesial and distal surface, and there is significant difference. The results demonstrate that ultrasonic curet alone is inadequate for thorough subgingival debridement and suggest that Ultrasonic curet with Gracey curet should be more effective.

• Korean Journal of Optics and Photonics
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• v.20 no.2
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• pp.94-101
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• 2009

A novel method for the reconstruction of 3D shape and texture from elemental images has been proposed. Using this method, we can estimate a full 3D polygonal model of objects with seamless triangulation. But in the triangulation process, all the objects are stitched. This generates phantom surfaces that bridge depth discontinuities between different objects. To solve this problem we need to connect points only within a single object. We adopt a segmentation process to this end. The entire process of the proposed method is as follows. First, the central pixel of each elemental image is computed to extract spatial position of objects by correspondence analysis. Second, the object points of central pixels from neighboring elemental images are projected onto a specific elemental image. Then, the center sub-image is segmented and each object is labeled. We used the normalized cut algorithm for segmentation of the center sub-image. To enhance the speed of segmentation we applied the watershed algorithm before the normalized cut. Using the segmentation results, the subdivision process is applied to pixels only within the same objects. The refined grid is filtered with median and Gaussian filters to improve reconstruction quality. Finally, each vertex is connected and an object-based triangular mesh is formed. We conducted experiments using real objects and verified our proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.438-456
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• 2010

Iris recognition uses a unique iris pattern of user to identify person. In order to enhance the performance of iris recognition, it is reported that the diameter of iris region should be greater than 200 pixels in the captured iris image. So, the previous iris system used zoom lens camera, which can increase the size and cost of system. To overcome these problems, we propose a new method of enhancing the accuracy of iris recognition on low-resolution iris images which are captured without a zoom lens. This research is novel in the following two ways compared to previous works. First, this research is the first one to analyze the performance degradation of iris recognition according to the decrease of the image resolution by excluding other factors such as image blurring and the occlusion of eyelid and eyelash. Second, in order to restore a high-resolution iris image from single low-resolution one, we propose a new method based on multiple multi-layered perceptrons (MLPs) which are trained according to the edge direction of iris patterns. From that, the accuracy of iris recognition with the restored images was much enhanced. Experimental results showed that when the iris images down-sampled by 6% compared to the original image were restored into the high resolution ones by using the proposed method, the EER of iris recognition was reduced as much as 0.133% (1.485% - 1.352%) in comparison with that by using bi-linear interpolation