• 한국표면공학회지
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• 제56권6호
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• pp.353-370
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• 2023

Corrosion detection and analysis is a very important topic in reducing costs and preventing disasters. Recently, image processing techniques have been widely applied to corrosion identification and analysis. In this work, we briefly introduces traditional image processing techniques and machine learning algorithms applied to detect or analyze corrosion in various fields. Recently, machine learning, especially CNN-based algorithms, have been widely applied to corrosion detection. Additionally, research on applying machine learning to region segmentation is very actively underway. The corrosion is reddish and brown in color and has a very irregular shape, so a combination of techniques that consider color and texture, various mathematical techniques, and machine learning algorithms are used to detect and analyze corrosion. We present examples of the application of traditional image processing techniques and machine learning to corrosion detection and analysis.

• Imaging Science in Dentistry
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• 제45권2호
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• pp.81-87
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• 2015

Purpose: Contrast, sharpness, enhancement, and density can be changed in digital systems. The important question is to what extent the changes in these variables affect the accuracy of caries detection. Materials and Methods: Forty eight extracted human posterior teeth with healthy or proximal caries surfaces were imaged using a photostimulable phosphor (PSP) sensor. All original images were processed using a six-step method: (1) applying "Sharpening 2" and "Noise Reduction" processing options to the original images; (2) applying the "Magnification 1:3" option to the image obtained in the first step; (3) enhancing the original images by using the "Diagonal/"option; (4) reviewing the changes brought about by the third step of image processing and then, applying "Magnification 1:3"; (5) applying "Sharpening UM" to the original images; and (6) analyzing the changes brought about by the fifth step of image processing, and finally, applying "Magnification 1:3." Three observers evaluated the images. The tooth sections were evaluated histologically as the gold standard. The diagnostic accuracy of the observers was compared using a chi-squared test. Results: The accuracy levels irrespective of the image processing method ranged from weak (18.8%) to intermediate (54.2%), but the highest accuracy was achieved at the sixth image processing step. The overall diagnostic accuracy level showed a statistically significant difference (p=0.0001). Conclusion: This study shows that the application of "Sharpening UM" along with the "Magnification 1:3" processing option improved the diagnostic accuracy and the observer agreement more effectively than the other processing procedures.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권3호
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• pp.188-193
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• 2017

영상 장비가 발전하고 고화질 이미지의 사용량이 많아짐에 따라 이를 병렬화하여 빠르게 처리하는 방법이 많이 연구되고 있다. 본 논문은 OpenCL을 사용한 이미지 처리 프로그램이 하드웨어에 관계없이 최적의 성능을 내도록 하는 방법을 제시한다. OpenCL은 계산 디바이스의 아키텍처에 따라 적절한 병렬화 방법과 워크그룹 크기를 개발자가 실험을 통해 찾아야 한다. 하지만 이는 시간적, 자원적 한계가 있다. 본 논문에서는 대상 하드웨어에 최적화된 병렬화 방법과 워크그룹 크기를 프로파일링을 통해 자동으로 선택하는 방법을 제안한다. 또한 OpenCL을 사용한 이미지 처리는 입력 이미지의 크기에 따라 순차코드 보다 성능이 좋을 수도 있고 안좋을 수도 있다. 본 논문에서는 OpenCL코드의 성능이 순차코드 성능보다 좋아지는 시점의 이미지 크기를 자동으로 검색하여 OpenCL을 사용할지 기존의 순차코드를 사용할지 결정하는 이미지 크기 threshold를 설정하는 방법을 제시한다. 이를 통해 이미지 처리 프로그램이 임의의 하드웨어에서 이미지 크기에 상관없이 항상 최적의 성능을 보이는 것을 확인했다.

• 한국축산시설환경학회지
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• 제7권3호
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• pp.183-190
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• 2001

본 연구는 영상처리를 통한 보다 간편하고 정확한 젖소의 체중측정을 위해 수행되었다. 카메라와 개인용 컴퓨터를 이용하여 젖소의 영상을 받은 후 이의 화소 값들을 이용하였으며, 또한 여러 가지 방법으로 체중과의 관계를 회귀분석 방법을 하였다. 1. 본 실험의 결과 다중회귀식에 의한 계산체중, 화소표면적, 부피와 체증과의 상관계수는 각각 0.9424, 0.9439, 0.9651로 나타났으며, 젖소의 체중과 상관관계도가 높았다. 2. 실험에 이용된 젖소의 개체수를 50두이었지만, 각각 상태별 체형의 차이고 인하여 일관된 회귀식을 적용하기에는 정확도 문제에서 다소 문제가 있었다. 그래서 각 개체군으로 나누어서 연구할 필요가 있을 것으로 판단되었다. 3. 젖소의 체중 계측시간은 10초에 불과하지만 실험장치까지의 유도과정은 편균 한 마리에 10분 정도가 소요되었다.

• 전기전자학회논문지
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• 제27권4호
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• pp.494-500
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• 2023

영상처리는 현재 다양한 분야에서 활용되고 있다. 그중 자율주행 자동차, 의료 영상처리, 로봇 제어 등은 빠른 영상처리 응답 속도가 필요하다. 이를 충족하기 위해 실시간 처리를 위한 하드웨어 설계가 활발히 연구되고 있다. 하드웨어 처리 속도는 입력 영상의 크기 외에도, 이미지에서 라인과 프레임을 구분하는 비활성화 영상 공백 구간의 크기에 영향을 받는다. 본 논문에서는 비활성화 영상 공백 구간과 밀접한 관련이 있는 라인메모리 유형에 따라 세 가지 스케일러 구조를 설계한다. 이 구조들은 Verilog 표준 언어를 사용하여 하드웨어로 설계되고, Xilinx Vivado 2023.1을 이용하여 field programmable gate array 환경에서 논리회로로 합성된다. 합성된 결과는 실시간 처리할 수 있는 표준 이미지 크기를 비교하면서 프레임 레이트 분석에 사용된다.

• 한국가시화정보학회지
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• 제6권2호
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• pp.20-27
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• 2008

The color sorting technique utilizing the image processing method is very applicable tool to analyze motion of a free-falling object in many agricultural and industrial research fields. In the present study, we have developed an image processing system and algorithm to sort good quality rice grains effectively from the bad ones. The system employs a high speed rate line-scan CCD camera with 2K-pixels and worked with a high speed DSP and FPGA in-line. It can accumulate acquired line-scan image data and visualize each grain image clearly. As a result, we can easily calculate the number of pixels occupied by grain(=grain size), gray level and its correct position by visualizing grain images rapidly.

• 전기학회논문지
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• 제57권2호
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• pp.294-302
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• 2008

In this paper, we present a new image up-sampling method which registers low resolution images to the high resolution grid when Bayesian super-resolution image processing is performed. The proposed up-sampling method interpolates high-resolution pixels using high-frequency data lying in all the low resolution images, instead of up-sampling each low resolution image separately. The interpolation is based on B-spline non-uniform re-sampling, adjusted for the super-resolution image processing. The experimental results demonstrate the effects when different up-sampling methods generally used such as zero-padding or bilinear interpolation are applied to the super-resolution image reconstruction. Then, we show that the proposed hybird up-sampling method generates high-resolution images more accurately than conventional methods with quantitative and qualitative assess measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4375-4388
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• 2018

To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.503-507
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• 2004

This paper is concerned with the measurement of low-frequency vibrations of structures using the image processing method. To measure the vibrations visually, the measurement system consists of a camera, an image grabber board, and a computer. The specific target installed on the structure is used to calculate the vibration of structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the size of image. In this paper, we discuss the methodology for the vibration measurement using the image processing method. The method enables us to measure the displacement directly without any contact. The resolution of the vibration measurement can be refined but limited to the sub centimeter displacement.

• Ocean Science Journal
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• 제40권4호
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• pp.213-220
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• 2005

In this paper, image processing technique that reduces video images of buoy motion to yield time series of image coordinates of buoy objects will be investigated. The buoy motion images are noisy due to time-varying brightness as well as non-uniform background illumination. The occurrence of boats, wakes, and wind-induced white caps interferes significantly in recognition of buoy objects. Thus, semi-automated procedures consisting of object recognition and image measurement aspects will be conducted. These offer more satisfactory results than a manual process. Spectral analysis shows that the image coordinates of buoy objects represent wave motion well, indicating its usefulness in the analysis of wave characteristics.