• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.49-55
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• 2000

The semiconductor industry relies on digital optical imaging for the overlay metrology of integrated circuit patterns. One critical performance demand in the particular application of digital imaging is placed on the edge resolution that is defined as the smallest detectable displacement of an edge from its image acquired in digital from. As the critical feature size of integrated circuit patterns reaches below 0.35 micrometers, the edge resolution is required to be less than 0.01 micrometers. This requirement is so stringent that fundamental behaviors of digital optical imaging need to be explored especially for the precision coordinate metrology. Our investigation reveals that the edge resolution shows quasi-random characteristics, not being simply deduced from relevant opto-electronic system parameters. Hence, a stochastic upper bound analysis is made to come up with the worst edge resolution that can statistically well predict actual indeterminate edge resolutions obtained with high magnification microscope objectives.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.381-384
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• 2003

Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve the problem, we propose the edge enhanced error diffusion using the edge information of the original images. The edge enchanted weights is computed by adding local characteristic weights and input pixels multiplied a constant. Also, we combined the edge enhanced method with the adaptive error diffusion using human spatial and frequency perception characteristic. The performance of the proposed method is compared with conventional method by measuring the edge correlation. The halftoned images applied the proposed method get more fine quality due to the enchanced edge and better quality in halftoned image. And the detailed edge is preserved in the halftoned images by the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1074-1084
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• 1995

In this paper, we investigate edge extraction and segmentation of range images. We first discuss problems that arise in the conventional region-based segmentation methods and edge-based ones using principal curvatures, then we propose an edge-based algorithm. In the proposed algorithm, we extract edge contours by using the Gaussian filter and directional derivatives, and segment a range image based on extracted edge contours, Also we present the problem that arises in the conventional thresholding, then we propose a new threshold selection method. To solve the problem that local maxima of the first- and second- order derivatives gather near step edges, we first find closed roof edge contours, fill the step edge region, and finally thin edge boundaries. Computer simulations with several range images show that the proposed method yields better performance than the conventional one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.199-207
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• 2001

In this paper, we suggest an edge-based surface segmentation algorithm of 3D image using curvature. For the first, in this proposed method, we approximate 3D depth data to second order curves by each scan line and decide splitting points of 3D edges by curvature of the approximated curves. And finally make a group as 3D surface with the region of input image by the 3D edges. In the conventional algorithms, there are some difficulties in detecting 3D edge with the separated processes for the jump edge and the crease edge and especially, in deciding the ambiguous discontinuity of surface directions about the crease edge. The proposed algorithm decides curvature discontinuity using curvature which is simply calculated by a geometrical approximation. Furthermore, the algorithm has a cooperated process to calculate the jump and crease edges. The results of computer simulations with several 3D images show that the proposed method yields better performance as comparing with the conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1142-1147
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• 2022

The edges of image should be detected first so that the objects in the image can be identified. An hardware-implemented edge detection algorithm outperforms its software version. Sobel operation is the most suitable algorithm for an hardware implementation of edge detection. And lots of works have been done to perform Sobel operations efficiently on FPGA-based hardware. This work proposes how to implement fast edge detection circuit on FPGA, which is based on the conventional circuit for edge detection using Sobel operator. The newly proposed circuit is suitable for processing images when the images are stored in memory devices and outperforms the conventional one with little additional FPGA resources. Both the conventional circuit and the proposed circuit were implemented on an FPGA. And the result showed that the proposed circuit almost doubles the performance in processing images and needs little additional FPGA resources.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.327-334
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• 2006

The aerial photos need in a simple object such as cartography and ground cover classification and also in a social objects such as the city plan, environment, disaster, transportation etc. However, the shadow, which includes when taking the aerial photos, makes a trouble to interpret the ground information, and also users, who need the photos in their field tasks, have a restriction. Generally the shadow occurs by the building and surface topography, and the detail cause is by changing of the illumination in an area. For removing the shadow this study uses the single image and processes the image without the source of image and taking situation. Also, applying the entropy minimization method it generates the 1-D gray-scale invariant image for creating the shadow edge mask and using the Canny edge detection creates the shadow edge mask, and finally by filtering in Fourier frequency domain creates the intrinsic image which recovers the 3-D color information and removes the shadow.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.407-414
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• 2014

The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.601-612
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• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.1-11
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• 2021

This paper presents a procedure to extract lane line models using a set of proposed methods. Firstly, an image warping method based on homography is proposed to transform a target image into an image which is efficient to find lane pixels within a certain region in the image. Secondly, a method to use the combination of the results of edge detection and HSL (Hue, Saturation, and Lightness) transform is proposed to detect lane candidate pixels with reliability. Thirdly, erroneous candidate lane pixels are eliminated using a selection area method. Fourthly, a method to fit lane pixels to quadratic polynomials is proposed. In order to test the validity of the proposed procedure, a set of black-box images captured under varying illumination and noise conditions were used. The experimental results show that the proposed procedure could overcome the problems of color-only and edge-only based methods and extract lane pixels and model the lane line geometry effectively within less than 0.6 seconds per frame under a low-cost computing environment.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.138-146
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• 2018

In this paper, we describe an algorithm for extracting depth information from a single image based on CNN. When acquiring three-dimensional information from a single two-dimensional image using a deep-learning technique, it is difficult to accurately predict the edge portion of the depth image because it is a part where the depth changes abruptly. in this paper, we introduce the concept of pixel-wise confidence to take advantage of these characteristics. We propose an algorithm that estimates depth information from a highly reliable flat part and propagates it to the edge part to improve the accuracy of depth estimation.