• Journal of the Optical Society of Korea
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• v.16 no.2
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• pp.127-132
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• 2012

This study discusses photoresist forming using a composite grayscale to fabricate a Fresnel lens. Grayscale lithography is a common production method used to facilitate the forming of lenses with different curvatures and depths. However, this approach is time consuming and expensive. This study proposes a method for overcoming these obstacles by integrating a digital micromirror device and microscope to supplant the traditional physical grayscale mask. This approach provides a simple and practical maskless optical lithography system. According to the results, the two adjacent grayscales displayed substantial differences between the high grayscale and influence the low grayscale that ultimately affected photoresist formation. Furthermore, we show that change of up to 150% in the slope can be achieved by changing the grayscale gradient in the central zone and the ring profile. The results of the optical experiment show a focus change with different gray gradients.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.378-391
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• 2010

In this paper, it is tested that an individual is able to be identified with finger face images and the results are presented. Special operators, FFG(Facet Function Gradient) masks by which the gradient of a facet function fit on a gray levels of image patches can be computed are used and a new procedure named F-algorithm is introduced to match the finger face images. The finger face image is divided into the equal subregions and each subregions are divided into equal patches with this algorithm. The FFG masks are used for convolution operation over each patch to produce scalar values. These values from a feature matrix, and the identity of fingers is determined by a norm of the elements of the feature matrices. The distribution of the norms shows conspicuous differences between the pairs of hand images of the same persons and the pairs of the different persons. This is a result to prove the ability of discrimination with the finger face image. An identification rate of 95.0% is obtained as a result of the test in which 500 hand images taken from 100 persons are processed through F-algorithm. It is affirmed that the finger face reveals to be such a good biometrics as other hand parts owing to the ability of discrimination and the identification rate.

• Korean Journal of Materials Research
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• v.10 no.3
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• pp.218-222
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• 2000

W-Ti film properties for X-ray absorber applications have been investigated with Ti composition have been investigated with Ti composition variation. W-Ti films were deposited by DC magnetron sputtering system. As the working pressure increases, film density decreases and film stress changes from compressive to tensile. The transition pressure (where the film stress in zero) and the stress gradient decrease by adding Ti into W-Ti(6.5 at.%) film shows the smallest stress gradient and transition pressure. It also shows high density ($17.7g/\textrm{cm}^3$) similar to that of pure-W ($17.8g/\textrm{cm}^3$) at the transition pressure. All the films show columnar structure, and its size decreases with increasing Ti composition. Surface roughness and thermal stability are improved by Ti-addition, resulting in a better property for X-ray absorber applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.455-461
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• 2002

This paper presents a new parametric log line equation of polar form for Hough transform in log-polar plane, in which it can remove the well-known unboundedness problem of Hough parameters. Bolduc's method is used to generate a log-polar image dividing the fovea and periphery from a Cartesian image. Edges of the fovea and periphery are detected by using the Sobel mask and the proposed space-variant gradient mask, and are combined in the log-polar plane. The sampled points that might constitute a log line are quite sparse in a deep peripheral region due to severe under-sampling, which is an inherent property of LPM. To cope with such under-sampling, we determine the values of cumulative cells in Hough space by using the space-variant weighting. In our experiments, the proposed method demonstrates its validity of detecting not only the lines passing through both the fovea and periphery but also the lines in a deep periphery.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

• Journal of Institute of Convergence Technology
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• v.5 no.2
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• pp.27-32
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• 2015

Air intakes are an essential component of aircraft engines. They are mainly used to offer uniform airflows to engine faces. Fighter aircraft have to mask the engine face inside the fuselage in order to reduce the Radar Cross Section(RCS). Therefore, offset intakes like a S-Duct are one of promising components for this purpose. During a fight, it is unavoidable that the flow will enter the intakes at some face angles other than zero. In this case, the performance of the aircraft engine will be influenced to the angle of incidence. In this study, the CFD analysis of the semi-circular S-Duct with AR(0.5,0) is performed to investigate the influence of the angle of incidence on the performance of the S-Duct using a distortion coefficient. To consider the adverse pressure gradient, a $k-{\omega}$ SST turbulence model is employed. The secondary flow and flow separation are observed for all computational cases. It is found that the positive incidence angle produces the best performances.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.26-31
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• 2010

We proposed a new directional edge based interpolation, DEBI, by combining two weighted directional information to reduce blurred edges and annoying artifacts. Four isotropic gradient masks are employed in defining edge directions and they are proven to hold a first order derivative relation with respect to a rotating coordinate. Two minimum gradients among four absolute directional results are shown to be sufficient to describe slant edges efficiently. Compared with widely used bilinear and bicubic interpolation methods, the proposed algorithm results in a noticeable improvement along edge area.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.218-223
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• 2013

The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.111-122
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• 2021

Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.