• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.225-230
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• 2015

In this paper, we propose an effective real-time visual loop closure detector, VILODE, which makes use of key frames and bag of visual words (BoW) based on SURF feature points. In order to determine whether the camera has re-visited one of the previously visited places, a loop closure detector has to compare an incoming new image with all previous images collected at every visited place. As the camera passes through new places or locations, the amount of images to be compared continues growing. For this reason, it is difficult for a visual loop closure detector to meet both real-time constraint and high detection accuracy. To address the problem, the proposed system adopts an effective key frame selection strategy which selects and compares only distinct meaningful ones from continuously incoming images during navigation, and so it can reduce greatly image comparisons for loop detection. Moreover, in order to improve detection accuracy and efficiency, the system represents each key frame image as a bag of visual words, and maintains indexes for them using DBoW database system. The experiments with TUM benchmark datasets demonstrates high performance of the proposed visual loop closure detector.

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.2
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• pp.139-143
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• 2010

Two-dimensional(2D) images like Multi Planar Reconstruction(MPR) Image or Maximum Intensity Projection(MIP) were used for the purpose of diagnosis, but MPR image's quality were limited due to its superior limit of Z-axis ability to produce permitted radiation exposure virtuous in the permitted time limit from the existing Spiral CT. However, in company with the development of the Multi Detector Computed Tomography(MDCT), we were able to get the Data with the equal amount of Voxel, also get varied reconstructions as in the aspect of our needs. This present study propose a reconstruction technique which is to extract a field using Region of interest(ROI) segmentation method for improvement of the quality of the medical image and after that reconstruct the concerned part using the four-directed symmetry method of the oval, than using the reconstructed data, reorganize the image by using the Curved MPR method. If current proposed method is used, it is highly effective because of its ability to accurately display the disease concerned part, which will reduce the decoding time and also effectively provide information based on the accuracy of the decode.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.291-296
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• 2015

In this paper, we propose a new confidence measure using pixel selection for eye detection and design a hybrid eye detector. For this, we produce sub-images by applying a pixel selection method to the eye patches and construct the BDA(Biased Discriminant Analysis) feature space for measuring the confidence of the eye detection results. For a hybrid eye detector, we select HFED(Haar-like Feature based Eye Detector) and MFED(MCT Feature based Eye Detector), which are complementary to each other, as basic detectors. For a given image, each basic detector conducts eye detection and the confidence of each result is estimated in the BDA feature space by calculating the distances between the produced eye patches and the mean of positive samples in the training set. Then, the result with higher confidence is adopted as the final eye detection result and is used to the face alignment process for face recognition. The experimental results for various face databases show that the proposed method performs more accurate eye detection and consequently results in better face recognition performance compared with other methods.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.329-335
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• 2010

Digital imaging detectors can use a variety of detection materials to convert X-ray radiation either to light or directly to electron charge. Many detectors such as amorphous silicon flat panels, CCDs, and CMOS photodiode arrays incorporate a scintillator screen to convert x-ray to light. The digital radiography systems based on semiconductor detectors, commonly referred to as flat panel detectors, are gaining popularity in the clinical & hospital. The X-ray detectors are described between a-Silicon based indirect type and a-Selenium based direct type. The DRS of detectors is used to convert the x-ray to electron hole pairs. Image processing is described by specific image features: Latitude compression, Contrast enhancement, Edge enhancement, Look up table, Noise suppression. The image features are tuned independently. The final enhancement result is a combination of all image features. The parameters are altered by using specific image features in the different several hospitals. The image in a radiological report consists of two image evaluation processes: Clinical image parameters and MTF is a descriptor of the spatial resolution of a digital imaging system. We used the edge test phantom and exposure procedure described in the IEC 61267 to obtain an edge spread function from which the MTF is calculated. We can compare image in the processing parameters to change between original and processed image data. The angle of the edge with respect to the axes of detector was varied in order to determine the MTF as a function of direction. Each MTF is integrated within the spatial resolution interval of 1.35-11.70 cycles/mm at the 50% MTF point. Each image enhancement parameters consists of edge, frequency, contrast, LUT, noise, sensitometry curve, threshold level, windows. The digital device is also shown to have good uniformity of MTF and image parameters across its modality. The measurements reported here represent a comprehensive evaluation of digital radiography system designed for use in the DRS. The results indicate that the parameter enables very good image quality in the digital radiography. Of course, the quality of image from a parameter is determined by other digital devices in addition to the proper clinical image.

• Journal of Radiation Protection and Research
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• v.45 no.1
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• pp.35-44
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• 2020

Background: Cadmium zinc telluride (CZT) is a promising material because of a high detection efficiency, good energy resolution, and operability at room temperature. However, the cost of CZT dramatically increases as its size increases. In this study, to achieve a large effective volume with relatively low cost, an array structure comprised of individual virtual Frisch-grid CZT detectors was proposed. Materials and Methods: The prototype consisted of 2 × 2 CZTs, a holder, anode and cathode printed circuit boards (PCBs), and an application-specific integrated circuit (ASIC). CZTs were used and the non-contacting shielding electrode method was applied for virtual Frisch-grid effect. An ASIC was used, and the holder and the PCBs were fabricated. In the current system, because the CZTs formed a common cathode, a total of 5 channels were assigned for data processing. Results and Discussion: An experiment using ¹³⁷Cs at room temperature was conducted for 10 minutes. Energy and timing information was acquired and the depth of interaction was calculated by the timing difference between the signals of both electrodes. Based on obtained three-dimensional position information, the energy correction was carried out, and as a result the energy spectra showed the improvements. In addition, a Compton image was reconstructed using the iterative method. Conclusion: The virtual Frisch-grid CZT detector based on the array structure was developed and the energy spectra and the Compton image were successfully acquired.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.379-382
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• 2002

Lately, intensifying screen of the $CaWO_4$ is used to medical treatment and diagnosis of the image. In this paper, we investigated transmission fraction and mass attenuation coefficient of $CaWO_4$ screen about diagnostic x-ray of low energy using MCNP 4C code. Experimentally, for 0.9 mm-$CaWO_4$ screen, the absorbable rate of diagnostic x-ray is more than 95%. according to kVp, the experimental value of mass attenuation coefficient is in a1most agreement with an corrected estimate value of MCNP and the deviation of experimental values is less than ${\pm}7%$. Using the MCNP code through this paper, we can make an estimate of signal and design for construction of the CaWO4/a-Se based digital x-ray image detector and make a good use of the foundation data for development of other materials.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.732-734
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• 2003

In the middle -resolution remote sensing, the Ground Sampled Distance(GSD) sensed and sampled by the detector is generally larger than the size of objects(or materials) of interest, in which case several objects are embedded in a single pixel and cannot be detected spatially. This study is intended to solve this problem of a hyperspectral data with high spectral resolution. We examined the detection algorithm, Linear Spectral Mixing Model, and also made a test on the Hyperion data. To find class Endmembers, we applied two methods, Spectral Library and Geometric Model, and compared them with each other.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1001-1007
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• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.37-41
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• 2003

We have developed a seeing monitoring system and measured seeing variation of the Bohyunsan Optical Astronomy Observatory (BOAO) and the Sobaeksan Optical Astronomy Observatory (SOAO) using a small telescope system. Our seeing monitoring system is similar to the differential image motion monitor (DIMM) installed at the ESO. The ooly difference between the BOAO and the SOAO seeing monitoring system is a detector system, a video camera at the BOAO and ST-4 camera at the SOAO. We confirmed that the seeing monitoring system at the SOAO can measure average seeing size inspite of its simple detector system. From the BOAO seeing measurement, we found that the seeing size changes fast. We expect that our seeing monitoring system could be used for real time seeing monitoring after some improvement, and the data to be obtained would be very useful when we build adaptive optic system in the future.