• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5643-5656
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• 2016

The detection accuracy of steganalysis depends on many factors, including the embedding algorithm, the payload size, the steganalysis feature space and the properties of the cover source. In practice, the cover source mismatch (CSM) problem has been recognized as the single most important factor negatively affecting the performance. To address this problem, we propose a new framework for blind, universal steganalysis which uses traditional steganalyst features. Firstly, cover images with the same statistical properties are searched from a reference image database as aided samples. The test image and its aided samples form a whole test set. Then, by assuming that most of the aided samples are innocent, we conduct outlier detection on the test set to judge the test image as cover or stego. In this way, the framework has removed the need for training. Hence, it does not suffer from cover source mismatch. Because it performs anomaly detection rather than classification, this method is totally unsupervised. The results in our study show that this framework works superior than one-class support vector machine and the outlier detector without considering the image retrieval process.

• 한국위성정보통신학회논문지
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• 제12권2호
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• pp.56-60
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• 2017

본 논문은 영상처리 기반의 낙상 감지 알고리즘의 설계 및 구현에 관한 내용을 기술한다. 영상처리 기반의 낙상 감지 알고리즘은 카메라로 획득한 입력 영상을 그레이 스케일 변환 후 배경차분과 이진화를 통해 객체를 분리하고, 라벨링을 통해 인체를 인식한다. 인식된 인체는 출력 영상으로 확인이 가능하며 낙상을 감지하게 되면 알람이 발생한다. 컴퓨터 시뮬레이션을 통하여 제안한 알고리즘을 실험한 결과 90%의 검출율을 보여주었다. DSP 영상처리 보드에 구현한 시제품 시험을 통하여 기능을 검증함으로서 실용화 가능성을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• 정보보호학회논문지
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• 제32권2호
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• pp.381-390
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• 2022

기계학습 이미지 인식 기술의 발전에 따라 이를 악성코드 검출에 적용하는 방법이 연구되고 있다. 그 대표적인 접근법으로 악성코드 파일을 이미지로 변환하고 이를 CNN과 같은 딥러닝 네트워크에 학습시켜 악성코드 검출과 분류를 수행하는 연구가 진행되어 의미 있는 결과가 발표되고 있다. 본 연구에서는 기계학습을 사용한 악성코드 검출에 효과적인 이미지 생성방법을 제시하고자 한다. 이를 위하여 이미지 생성의 여러 선택 요소에 따른 악성코드 검출의 성능을 실험하고 분석하였으며, 그 결과를 반영하여 명령어 흐름의 특성을 좀 더 명확하게 나타낼 수 있는 선형적 이미지 생성방법을 제시하고 이 방법이 악성코드 검출의 정밀도를 높일 수 있음을 실험을 통하여 보였다.

• 센서학회지
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• 제31권2호
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• pp.131-137
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• 2022

Crimes related to illegal cameras are steadily increasing and causing social problems. Owing to the development of camera technology, the miniaturization and high performance of illegal cameras have caused anxiety among many people. This study is for detecting hidden cameras effectively such that they could not be easily detected by human eyes. An image sensor-based module with 940 nm wavelength infrared detection technology was developed, and an image processing algorithm was developed to selectively detect illegal cameras. Based on the Android smartphone environment, image processing technology was applied to an image acquired from an infrared camera, and a detection sensor module that is less sensitive to ambient brightness noise was studied. Experiments and optimization studies were conducted according to the Gaussian blur size, adaptive threshold size, and detection distance. The performance of the infrared image-based illegal camera detection sensor module was excellent. This is expected to contribute to the prevention of crimes related to illegal cameras.

• 인터넷정보학회논문지
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• 제13권3호
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• pp.17-22
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• 2012

본 논문에서는 APD(Avalanche photodiode)센서와 LED조명 및 광섬유 도파관(Fiber optic waveguide)를 이용한 광전((光電, Photoelectric) 영상 검출시스템을 제안한다. 제안한 핀홀(Pinhole) 검출시스템은 100미크론의 핀홀을 1,000mpm(meter per minute)의 속도로 검출할 수 있다. 아울러, 영상검출 알고리듬을 통해 검출된 핀홀의 위치와 크기 별로 분류할 수 있는 SQL기반의 DB결과를 분석함으로서 영상검출시스템의 검출성능이 개선되었다.

• 한국멀티미디어학회논문지
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• 제16권4호
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• pp.411-417
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• 2013

In this paper, we proposed a fast detection method of copy-move forgery image based on low frequency coefficients of the DCT coefficients. We proposed a new matching criterion of copy-moved forgery image detection (MCD) using discrete cosine transform. For each $8{\times}8$ pixel block, the DCT transform is calculated. Our algorithm uses low frequency four (DC, 3 AC coefficient) and six coefficients (DC, 5 AC coefficients) of DCT per $8{\times}8$ pixel block. Our algorithm worked block matching for DCT coefficients of the $8{\times}8$ pixel block is slid by one pixel along the image from the upper left corner to the lower right corner. Our algorithm can reduce computational complexity more than conventional copy moved forgery detection algorithms.

• 한국통신학회논문지
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• 제12권4호
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• pp.405-413
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• 1987

본 논문은 2-차원에서 3가지 형태(Square, Cross, X-shape)의 메디안 필터를 사용하여 레이다 영상의 원영상을 유지하면서 잡음을 제거하여 영상을 개선하고, 연산자를 적용하여 경계를 검출한다. 레이다 영상의 특성에서 곡선 부분이 많으므로 제안된 경계 검출 연산자에 의한 결과와 기존의 경계검출 방법인 Sobel, Prewitt, Robert, Laplacian. Kirsch의 결과를 비교한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.166-173
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• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권11호
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• pp.634-643
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• 2003

This paper presents a method for detecting skin tumors on chicken carcasses using hyperspectral images. It utilizes both fluorescence and reflectance image information in hyperspectral images. A detection system that is built on this concept can increase detection rate and reduce processing time, because the procedure for detection can be simplified. Chicken carcasses are examined first using band ratio FCM information of fluorescence image and it results in candidate regions for skin tumor. Next classifier selects the real tumor spots using PCA components information of reflectance image from the candidate regions. For the real world application, real-time processing is a key issue in implementation and the proposed method can accommodate the requirement by using a limited number of features to maintain the low computational complexity. Nevertheless, it shows favorable results and, in addition, uncovers meaningful spectral bands for detecting tumors using hyperspectral image. The method and findings can be employed in implementing customized chicken tumor detection systems.