• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.71-73
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• 2021

본 논문에서는 Scene Text Detection의 새로운 프레임워크인 TextFuseNet에 영상처리 관련 기술인 선명화 기법을 제안한다. Scene Text Detection은 야외 간판이나 표지판 등 불특정 배경에서 글자를 인식하는 기술이며, 그중 하나의 프레임워크가 TextFuseNet이다. TextFuseNet은 문자, 단어, 전역 기준으로 텍스트를 감지하는데, 여기서는 영상처리의 기술인 선명화 기법을 적용하여 TextFuseNet의 성능을 향상시키는 것이 목적이다. 선명화 기법은 기존 Sharpening Filter 방법과 Unsharp Masking 방법을 사용하였고 이 중 Sharpening Filter 방법을 적용하였을 때 AP가 0.9% 향상되었음을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.6-99
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• 2002

$\textbullet$ Contents 1 introduction $\textbullet$ Contents 2 The system implementation $\textbullet$ Contents 3 low \ulcornerlevel image processing $\textbullet$ Contents 4 scene sequence interpretation $\textbullet$ Contents 5 Implementation experimental result

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.75-80
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.498-506
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• 2003

A computer vision system applied to an intelligent safety vehicle has been required to be worked on a small sized real time special purposed hardware not on a general purposed computer. In addition, the system should have a high reliability even under the adverse road traffic environment. This paper presents a design and an implementation of an onboard hardware system taking into account for high speed image processing to analyze a road traffic scene. The system is mainly composed of two parts: an early processing module of FPGA and a postprocessing module of DSP. The early processing module is designed to extract several image primitives such as the intensity of a gray level image and edge attributes in a real-time Especially, the module is optimized for the Sobel edge operation. The postprocessing module of DSP utilizes the image features from the early processing module for making image understanding or image analysis of a road traffic scene. The performance of the proposed system is evaluated by an experiment of a lane-related information extraction. The experiment shows the successful results of image processing speed of twenty-five frames of 320$\times$240 pixels per second.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.56-64
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• 1997

An HDTV frame has 4~6 times more pixels than a DTV frame. In order to encode the HDTV image in real time, parallel processing architectures have been widely used in many HDTV codec developments. That is, an HDTV Image is divided into several subbands and each subband is encoded in parallel using some DTV level encoders. In this paper, we adopt an HDTV codec architecture which divides an HDTV frame into 4 subbands and propose a new scene change detection algorithm using local variance. In addition, a new adaptive multichannel rate control scheme which allocate target bits adaptively to each subband of the HDTV image based on the activities of subband images is suggested in this paper. The activities of subband images are calculated at scene change detection part and reused at the adaptive rate control part. The simulation results show that the proposed scene change detection algorithm detects the scene change of HDTV video very accurately. Also the suggested adaptive multichannel rate control scheme shows better performance than the rate control method which allocates target bits equally to each subbands of the HDTV image.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.777-785
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• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.441-448
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• 2016

In this paper, we propose a method that segments the image, extracts its slope and compensate it in the image that text and background are mixed. The proposed method uses morphology based preprocessing and extracts the edges using canny operator. And after segmenting the image which the edges are extracted, it excludes the areas which the edges are included, only uses the area which the edges are included and creates the projection histograms according to their various direction slopes. Using them, it takes a slope having the greatest edge concentrativeness of each area and compensates the slope of the scene. On extracting the slope of the mixed scene of the text and background, the method can get better results as 0.7% than the existing methods as it excludes the useless areas that the edges do not exist.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• Proceedings of the KSRS Conference
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• v.2
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• pp.780-783
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• 2006

The KOrea Multi-Purpose Satellite-2 (KOMPSAT-2) was launched in July 2006 and the main mission of the KOMPSAT-2 is a high resolution imaging for the cartography of Korea peninsula by utilizing Multi Spectral Camera (MSC) images. The camera resolutions are 1 m in panchromatic scene and 4 m in multi-spectral imaging. This paper provides an initial geometric accuracy assessment of the KOMPSAT-2 high resolution image without ground control points and briefly introduces the sensor model of KOMPSAT-2. Also investigated and evaluated the obtained 3-dimensional terrain information using the MSC pass image and scene images acquired from the KOMPSAT-2 satellite.