• 반도체디스플레이기술학회지
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• 제16권1호
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• pp.6-10
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• 2017

Recent enhancement in the still image acquisition devices has been widely perpetrated into the daily life of the common people. Due to this trend, the voluminous still images, that are produced and shared in the personal or the massive storage, need to controlled with effective and efficient management. The human-devised or system-generated still image identifiers used for the identification of the images are at risk in the situation of unexpected changing or eliminating of the identifiers. In this paper, we propose a parallel processing based method for still image identifier generation by utilizing the still image internal features.

• 기술사
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• 제16권4호
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• pp.15-19
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• 1983

Therefore the use of Hadamard transform in the image processing requires only the real number operations and results in the computational advantages. Recently, however, certain degradation aspects have been reported. In this paper we propose a WH matrixtwhich retains the main properties of Hadamard matrix. The actual improvement of the image transmission in the inner part of the picture has been demonstrated by the computer simulated image developments. The orthogonal transforms such as Hadamard transform offers a useful facility in the digital signal processing. As the size of the transmission block increases, however, the assignment of bits for each data must increase exponentially. Thus the SNR of the image tends to decline accordingly. As an attempt to increase the SNR, we propose the WH matrix whose elements are made of ${\pm}$1, ${\pm}$2, ${\pm}$3, ${\pm}$4, and the unitform is 8${\times}$8 matrix.

• IEIE Transactions on Smart Processing and Computing
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• 제2권3호
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• pp.140-147
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• 2013

We present a vaguelette-curvelet decomposition based image deblurring algorithm. We first perform denoising based on the hard-thresholding rule by estimating unknown curvelet coefficients. The proposed algorithm then calculates vaguelette functions by deconvolving the curvelet bases by the point spread function. Vaguelette transform is finally performed to make a clearly restored image. Since the proposed algorithm uses the curvelet transform to sensitively express the edges in all directions, it is possible to restore images with more naturally preserved edges in all directions.

• 대한전기학회논문지:전력기술부문A
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• 제48권5호
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• pp.658-663
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• 1999

2D sliced CT images hardly express the human disease in a space. This space expression can be reconstructed into 3D image by piling up the CT sliced image in succession. In medical image, in order to get the reconstructed 3D images, expensive system or much calculation time is needed. But by changing the method of reconstruction procedure and limit the range, the reconstruction time could be reduced. In this study, to reduce the processing time and memory, we suggested a method of interpolation and ray casting processing at the same time in a limited range. Such a limited range processing have advantages that we could reduce the unnecessary interpolation and ray casting. Through a experiment, it is founded that the reconstruction time and the memory was much reduced.

• 한국항공우주학회지
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• 제36권6호
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• pp.594-599
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• 2008

현재 국방과학연구소 수동 시험에서 생성된 영상데이터는 수작업에 의해 분석되어지고 있다. 이러한 방법은 관측자에 따라 정확성과 분석소요시간이 상이할 수 있다 . 본 논문에서는 개선된 영상데이터 처리와 분석을 위해 MATLAB을 기반으로 한 알고리즘을 제안하였다. 이 알고리즘은 왜곡 보정 , 그레이 레벨 변환, 노이즈 제거, 이진화를 하는 영상 전처리 과정, 와류 궤적을 계측하는 영상 분석 과정으로 구성되어 있다 . 수동 시험에서 획득된 영상데이터를 이용하여 테스트 한 결과 제안된 알고리즘은 기존 영상데이터 분석 방법에 비해 정확성과 실행속도가 향상되었다.

• Journal of Information Processing Systems
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• 제11권4호
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• pp.495-508
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• 2015

In this paper, a novel robust medical images watermarking scheme is proposed. In traditional methods, the added watermark may alter the host medical image in an irreversible manner and may mask subtle details. Consequently, we propose a method for medical image copyright protection that may remedy this problem by embedding the watermark without modifying the original host image. The proposed method is based on the visual cryptography concept and the dominant blocks of wavelet coefficients. The logic in using the blocks dominants map is that local features, such as contours or edges, are unique to each image. The experimental results show that the proposed method can withstand several image processing attacks such as cropping, filtering, compression, etc.

• 대한임베디드공학회논문지
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• 제14권3호
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• pp.133-142
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• 2019

The existing auxiliary communicating aids for the hearing-impaired have an inconvenience of using additional expensive sensing devices. This paper presents a hand image detection based algorithm to interpret the sign language of the hearing-impaired. The proposed sign language recognition system exploits the hand image only captured by the camera without using any additional gloves with extra sensors. Based on the hand image processing, the system can perfectly classify several numeric sign language representations. This work proposes a simple lightweight classification algorithm to identify the hand image of the hearing-impaired to communicate with others even further in an environment of complex background. Experimental results show that the proposed system can interpret the numeric sign language quite well with an accuracy of 95.6% on average.

• 한국분무공학회지
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• 제29권2호
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• pp.91-97
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• 2024

When investigating the droplet, spray, and impact of liquid on a solid plate, backlight imaging has been widely used to understand these phenomena. However, some previous studies have suffered from poor image quality. In this study, various combinations of image processing algorithms, such as white image correction, histogram equalization, CLAHE, Otsu's binarization, and multi-Otsu's binarization, have been applied to flash boiling spray images to enhance image quality for qualitative observation and semi-quantitative spray angle evaluation. To acquire images with high contrast for qualitative observation, applying CLAHE was effective, making small droplets and detailed shapes of the jet noticeable. However, when images were averaged to determine spray angle or penetration length based on intensity, this method induced artifact unphysical patterns, thus requiring careful consideration. Based on the algorithm proposed in this study, the spray angle variation according to injection pressure and temperature has been calculated, showing a reasonable trend.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.153-156
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• 2000

Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, Many researchers have been studying on extracting feature from color Information, because of its advantages. This paper proposes a feature and its extraction method based on color correlogram that is extracted from color information in an image. the proposed method is computed from the image segmented into two parts; the complex part and the plain part. Our experiments show that the performance of the proposed method is better as compared with that of the original color correlogram method.