• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.6
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• pp.272-275
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• 2004

A balanced single side-band (SSB) mixer employing a sub-harmonic configuration is designed for up and down conversions in K-band. The designed mixer uses anti-parallel diode (APD) pairs to effectively eliminate even harmonics of the local oscillator (LO) spurious signal. To reduce the odd harmonics of LO at the RF port, we employ a balanced configuration for LO. The fabricated chip shows 12$\pm$2dB of conversion loss and image-rejection ratio of about 20dB for down conversion at RF frequencies of 24-27.5GHz. As an up-conversion mode, the designed chip shows 12dB of conversion loss and image-rejection ratio of 20 ～ 25 dB at RF frequencies of 25 to 27GHz. The odd harmonics of the LO are measured below -37dBc.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.509-516
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.61-70
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• 2020

Convolutional Neural Networks (CNN) have been used extensively in recent times to solve image classification and segmentation problems. However, the use of CNNs in image super-resolution problems remains largely unexploited. Filter interpolation and prediction model methods are the most commonly used algorithms in super-resolution algorithm implementations. The major limitation in the above named methods is that images become totally blurred and a lot of the edge information are lost. In this paper, we analyze super resolution based on CNN and the wavelet transform super resolution method. We compare and analyze the performance according to the number of layers and the training data of the CNN.

• ETRI Journal
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• v.39 no.6
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• pp.841-850
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• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3207-3209
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• 2000

X-ray CT(Computed Tomography) has been a good modality for non-invasive diagnosis and recently, Conventional CT has been replaced rapidly with Spiral CT in recent. In X-ray CT, spiral scanning has various advantages such as better image quality, reduced scan time (in a single breath-hold), a lower x-ray dose. But, it requires very fast and high performance image processing system to reconstruct slice images from spiral scanning. This paper describes the fast image reconstruction techniques with filtered back projection from the viewpoints of fast algorithm as well as hardware implementation for real-time imaging.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.465-472
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• 2009

This paper proposes a multimodal information transformation system that converts the image information to the voice information to provide the sight impaired people with walking area and obstacles, which are extracted by an acquired image from a single CCD camera. Using a chain-code line detection algorithm, the walking area is found from the vanishing point and boundary of a sidewalk on the edge image. And obstacles are detected by Gabor filter of extracting vertical lines on the walking area. The proposed system expresses the voice information of pre-defined sentences, consisting of template words which mean walking area and obstacles. The multi-modal information transformation system serves the useful voice information to the sight impaired that intend to reach their destination. The experiments of the proposed algorithm has been implemented on the indoor and outdoor environments, and verified its superiority to exactly provide walking parameters sentences.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.52-57
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• 2004

In this paper, we propose a panorama-based object tracking scheme for wide-view surveillance systems that can detect and track moving objects with a pan-tilt camera. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion information. For the camera motion estimation, we calculate affine motion parameters for each frame sequentially with respect to its previous frame. The camera motion is robustly estimated on the background by discriminating between background and foreground regions. The modified block-based motion estimation is used to separate the background region. Each moving object is segmented by image subtraction from the mosaic background. The proposed tracking system has demonstrated good performance for several test video sequences.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.337-339
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• 2003

This paper describes the SAR geocoding module, which is the sub-module of a IRHIS ('Integrated RS s/w for High resolution satellite ImageS'): package of 'Development of High Resolution Satellite Image Processing Technique' project in Electronics and Telecommunications Research Institute (ETRI). The function of this module is following. 1) Orbit Type : ERS1/ERS2, RADARSAT 2) Data Format : SAR CEOS Format(Single Look Complex) 3) Function: - Geocode : Generate a map projected SAR image based on only orbit information - Orthorectify: Generate a rigorous geocoded SAR image with a DEM information In this paper, we briefly describe the algorithm that is adopted to the functions, and component architecture.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.