• 전기전자학회논문지
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• 제22권3호
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• pp.578-584
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• 2018

이미지 분할은 영상의 해석과 이미지 인식 분야에서 다양한 방법으로 연구되고 있으며, 특정한 목적에 따른 이미지의 특성을 분리하기 위해 사용된다. 본 논문에서는 열화상 이미지의 특징점인 고온을 검출하여 이미지를 분할하는 알고리즘을 제안한다. 또한 연산속도의 향상을 위해 제안하는 알고리즘을 Zynq-7000 Evaluation Board 환경에서 FPGA Hardware Block Design을 진행하였다. 고온 검출 알고리즘은 16ms에서 0.001ms의 속도 향상을 보였으며 전체 블록은 50ms에서 0.322ms로 속도 향상을 보이는 것을 확인하였다. 또한 영상 테스트벤치를 사용하여 소프트웨어와 하드웨어 이미지에 대해 유사한 PSNR 결과를 입증하였다.

• Smart Structures and Systems
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• 제17권6호
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• 한국컴퓨터정보학회논문지
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• 제11권3호
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• pp.133-139
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• 2006

컴퓨터 정보기술의 발달로 멀티미디어 데이터가 급증하고 있다. 특히, 영상검색 분야에서는 영상 데이터의 신속, 정확한 처리 및 분석이 요구된다. 그러나 일반적으로 신속성과 정확성을 모두 보장하는 데는 어려움이 있다. 본 논문은 이러한 문제를 해결하기 위하여 유전자 알고리즘을 이용해 영상의 대표 특징치를 추출하는 알고리즘을 제안한다. 이 알고리즘은 영상이 가지고 있는 대표적인 특징치 뽑아냄으로써 검색의 신속성과 정확성을 보장한다. 영상의 특징으로는 색상과 질감을 사용하였다. 실험결과, 기존의 연구에 비해 제안된 특징 추출법이 더 좋은 정확성을 보임으로서 제안된 방법의 타당성을 입증하였다.

• Nuclear Engineering and Technology
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• 제55권12호
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• pp.4591-4596
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• 2023

Single-photon emission computed tomography SPECT image reconstruction methods have a significant influence on image quality, with filtered back projection (FBP) and ordered subset expectation maximization (OSEM) being the most commonly used methods. In this study, we proposed newly-designed adaptive non-blind deconvolution with a structural similarity (SSIM) index that can take advantage of the FBP and OSEM image reconstruction methods. After acquiring brain SPECT images, the proposed image was obtained using an algorithm that applied the SSIM metric, defined by predicting the distribution and amount of blurring. As a result of the contrast to noise ratio (CNR) and coefficient of variation evaluation (COV), the resulting image of the proposed algorithm showed a similar trend in spatial resolution to that of FBP, while obtaining values similar to those of OSEM. In addition, we confirmed that the CNR and COV values of the proposed algorithm improved by approximately 1.69 and 1.59 times, respectively, compared with those of the algorithm involving an inappropriate deblurring process. To summarize, we proposed a new type of algorithm that combines the advantages of SPECT image reconstruction techniques and is expected to be applicable in various fields.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.163-169
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• 2017

There are various algorithms evaluating a threshold for image segmentation. Among them, Otsu's algorithm sets a threshold based on the histogram. It finds the between-class variance for all over gray levels and then sets the largest one as Otsu's optimal threshold, so we can see that Otsu's algorithm requires a lot of the computation. In this paper, we improved the amount of computational needs by using estimated Otsu's threshold rather than computing for all the threshold candidates. The proposed algorithm is compared with the original one in computation amount and accuracy. we confirm that the proposed algorithm is about 29 times faster than conventional method on single processor and about 4 times faster than on parallel processing architecture machine.

• 한국통신학회논문지
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• 제21권3호
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• pp.564-575
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• 1996

Conventional decoding procedures have some problems in order to obtain reconstructed images with high speed. In this paper, the solutions of these are studied and a new fast decoding algorithm is proposed. The proposed algorithm uses a convergence criterion that is used to reduce the redundant iteration in the conventional method and to determine continuation of decoding. The initical image similar to roiginal image is estimated firstly in this algorithm. From the simulation resuls, the proposed algorithm is able to achieve the reconstructed image within 3-4 iteration under the objective criterion. Without any increment of the memory, the quality of the image reconstructed by the proposed algorithm has same quality asthe conventional method.

• 전자공학회논문지B
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• 제33B권8호
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• pp.81-95
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• 1996

In this paper, we propose a motio estiamtion algorithm using low-resolution quantization to reduce the computation of the full search algorithm. The proposed algorithm consists of the low-resolution search which determins the candidate motion vectors by comparing the low-resolution image and the full-resolution search which determines the motion vector by comparing the full-resolution image on the positions of the candidate motion vectors. The low-resolution image is generated by subtracting each pixel value in the reference block or the search window by the mean of the reference block, and by quantizing it is 2-bit resolution. The candidate motion vectors are determined by counting the number of pixels in the reference block whose quantized codes are unmatched to those in the search window. Simulation results show that the required computational cost of the proposed algorithm is reduced to 1/12 of the full search algorithm while its performance degradation is 0.03~0.12 dB.

• 한국가시화정보학회지
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• 제19권3호
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• pp.63-68
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• 2021

In this study, data was augmentation through the SinGAN algorithm using small image data, and defects in rubber O-rings were detected using the random forest algorithm. Unlike the commonly used data augmentation image rotation method to solve the data imbalance problem, the data imbalance problem was solved by using the SinGAN algorithm. A study was conducted to distinguish between normal products and defective products of rubber o-ring by using the random forest algorithm. A total of 20,000 image date were divided into transit and testing datasets, and an accuracy result was obtained to distinguish 97.43% defects as a result of the test.

• 전자공학회논문지
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• 제51권1호
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• pp.145-151
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• 2014

본 논문에서는 한 장의 영상에서 안개를 제거하는 알고리즘을 제안한다. 기존의 Dark Channel Prior(DCP) 알고리즘은 영상의 어두운 정보를 계산하여 전달량을 추정한 후, 매팅(matting) 기법을 사용하여 안개 영역을 보완하여 검출한다. 이 과정에서 블록현상이 발생하는 문제가 있으며 이로 인해 안개를 효율적으로 제거하는데 한계점이 있다. 이 문제를 해결하기 위해 본 논문에서는 Hidden Markov Random Field(HMRF) 와 Expectation-Maximization(EM) 알고리즘을 이용하여 매팅 과정에서 발생하는 블록문제를 해결하고자 하였다. 실험 결과를 통하여 제안한 방법은 기존 방법보다 안개제거에서 더 향상된 결과를 얻을 수 있음을 확인하였다.