• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.316-320
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• 2009

In this paper, a reference-free perceptual quality metric is proposed for image assessment. It measures the amount of overall blockiness and blurring in the image. And edge-oriented artifacts, such as ringing, mosaic and staircase noise are also considered. In order to give a single quality score, the individual artifact scores are adaptively combined according to the difference between the edge-oriented artifacts and other artifacts. The quality score obtained by the proposed algorithm shows strong correlation with the MOS values by VQEG.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.25-34
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• 1999

In this paper, an algorithm is presented to recognize lane and obstacles based on highway road image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, edge detection, and identification of lanes. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction and the presence of absence of an obstacle. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing lane and obstacles. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning of assistance system

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1214-1218
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• 2006

This paper presents method to speed up processing time in construction of panoramic images. The method based on invariant feature uses image down-scaling and image edge information. Reducing image size and applying feature descriptor to image portions superimposed with edge causes to reduce the number of features and to improve processing speed. In the experiments, it was shown that the proposed method was 3.26$\sim$13.87% shorter in processing time than the exiting method fer 24-bit color images of 640$\times$480 size.

• Annual Conference of KIPS
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• 2000.04a
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• pp.1042-1046
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• 2000

본 논문에서는 질감 정보를 나타낼 수 있는 Block-based 에지 히스토그램과 색상 정보를 표현할 수 있는 DCT 를 이용한 칼라 영상 검색 방법을 제안한다. 제안된 방법은 최소의 특징량으로 최대의 검색효율을 얻기 위해 YCbCr 칼라 모델상에서 Y 영상으로부터는 전체적인 영상에 대한 히스토그램과 에지 히스토그램을 특징량으로 추출하고 Cb, Cr 영상으로부터는 DCT 계수를 특징량으로 추출하여 칼라 영상을 검색한다. 이는 칼라와 질감을 동시에 고려하면서 특징량의 크기가 적어 웹, 대용량 검색 시스템 및 동영상 검색에 적합하다. 성능 평가는 MPEG-7 의 칼라 특징자들의 성능평가를 위해 사용된 S1 및 S3 그룹 영상을 대상으로 실험하였으며 제안한 복합 특징량은 칼라 영상 검색에서 우수한 성능을 나타냄을 실험으로 확인 하였다.

• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.421-424
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• 2022

Hough transform is a representative algorithm for detecting straight lines in an edge image. It corresponds the parameters of straight lines that may occur in the edge pixel into a parameter space, and detects valid parameters satisfying a given condition as straight lines. In general Hough transform, the parameters of the line are calculated with the image origin as the reference point. However, in this paper, the Hough transform based on the image center as a reference point is performed and its performance is compared and analyzed with the conventional Hough transform.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.166-171
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• 2023

With significant advancements in the field of artificial intelligence, many novel algorithms and technologies have emerged. Currently, AI painting can generate high-quality images based on textual descriptions. However, it is often challenging to control details when generating images, even with complex textual inputs. Therefore, there is a need to implement additional control mechanisms beyond textual descriptions. Based on ControlNet, this passage describes a combined utilization of various local controls (such as edge maps and depth maps) and global control within a single model. It provides a comprehensive exposition of the fundamental concepts of ControlNet, elucidating its theoretical foundation and relevant technological features. Furthermore, combining methods and applications, understanding the technical characteristics involves analyzing distinct advantages and image differences. This further explores insights into the development of image generation patterns.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.77-82
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• 2006

Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn't perceive a little variation of the spatial variation. The proposed method computes a spatialactivity, which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' Iuminance weighted according to the spatial positioning. The system also usesof edge enhancement (IEE), which is computed from the normalized spatial activitymultiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methodsand the edge of objects is preserved well. Also the performance of the preposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.113-117
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• 2007

In this paper, we propose a new method for determining automatically the size of the matching window using histogram of the gradient in order to improve the performance of stereo matching using one-meter resolution satellite imagery. For each pixel, we generate Flatness Index Image by calculating the mean value of the vertical or horizontal intensity gradients of the 4-neighbors of every pixel in the entire image. The edge pixel has high flatness index value, while the non-edge pixel has low flatness index value. By using the histogram of the Flatness Index Image, we find a flatness threshold value to determine whether a pixel is edge pixel or non-edge pixel. If a pixel has higher flatness index value than the flatness threshold value, we classify the pixel into edge pixel, otherwise we classify the pixel into non-edge pixel. If the ratio of the number of non-edge pixels in initial matching window is low, then we consider the pixel to be in homogeneous region and enlarge the size of the matching window We repeat this process until the size of matching window reaches to a maximum size. In the experiment, we used IKONOS satellite stereo imagery and obtained more improved matching results than the matching method using fixed matching window size.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.33-42
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• 2005

Identifying color codes needs precise color information of their constituents, and is far from trivial because colors usually suffer severe distortions throughout the entire procedures from printing to acquiring image data. To accomplish accurate identification of colors, we need a reliable segmentation method to separate different color regions from each other, which would enable us to process the whole pixels in the region of a color statistically, instead of a subset of pixels in the region. Color image segmentation can be accomplished by performing edge detection on component image(s). In this paper, we separately detected edges on component images from RGB, HSI, and YIQ color models, and performed mathematical analyses and experiments to find out a pair of component images that provided the best edge image when combined. The best result was obtained by combining Y- and R-component edge images.