• Title/Summary/Keyword: image analysis algorithm

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A New Robust Blind Crypto-Watermarking Method for Medical Images Security

  • Mohamed Boussif;Oussema Boufares;Aloui Noureddine;Adnene Cherif
    • International Journal of Computer Science & Network Security
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    • v.24 no.3
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    • pp.93-100
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    • 2024
  • In this paper, we propose a novel robust blind crypto-watermarking method for medical images security based on hiding of DICOM patient information (patient name, age...) in the medical imaging. The DICOM patient information is encrypted using the AES standard algorithm before its insertion in the medical image. The cover image is divided in blocks of 8x8, in each we insert 1-bit of the encrypted watermark in the hybrid transform domain by applying respectively the 2D-LWT (Lifting wavelet transforms), the 2D-DCT (discrete cosine transforms), and the SVD (singular value decomposition). The scheme is tested by applying various attacks such as noise, filtering and compression. Experimental results show that no visible difference between the watermarked images and the original images and the test against attack shows the good robustness of the proposed algorithm.

Developing Image Processing Program for Automated Counting of Airborne Fibers (이미지 처리를 통한 공기 중 섬유의 자동계수 알고리즘 프로그램 개발)

  • Choi, Sungwon;Lee, Heekong;Lee, Jong Il;Kim, Hyunwook
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.24 no.4
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    • pp.484-491
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    • 2014
  • Objectives: An image processing program for asbestos fibers analyzing the gradient components and partial linearity was developed in order to accurately segment fibers. The objectives were to increase the accuracy of counting through the formulation of the size and shape of fibers and to guarantee robust fiber detection in noisy backgrounds. Methods: We utilized samples mixed with sand and sepiolite, which has a similar structure to asbestos. Sample concentrations of 0.01%, 0.05%, 0.1%, 0.5%, 1%, 2%, and 3%(w/w) were prepared. The sand used was homogenized after being sieved to less than $180{\mu}m$. Airborne samples were collected on MCE filters by utilizing a personal pump with 2 L/min flow rate for 30 minutes. We used the NIOSH 7400 method for pre-treating and counting the fibers on the filters. The results of the NIOSH 7400 method were compared with those of the image processing program. Results: The performance of the developed algorithm, when compared with the target images acquired by PCM, showed that the detection rate was on average 88.67%. The main causes of non-detection were missing fibers with a low degree of contrast and overlapping of faint and thin fibers. Also, some duplicate countings occurred for fibers with breaks in the middle due to overlapping particles. Conclusions: An image detection algorithm that could increase the accuracy of fiber counting was developed by considering the direction of the edge to extract images of fibers. It showed comparable results to PCM analysis and could be used to count fibers through real-time tracking by modeling a branch point to graph. This algorithm can be utilized to measure the concentrations of asbestos in real-time if a suitable optical design is developed.

X-ray Image Processing for the Korea Red Ginseng Inner Hole Detection (II) - Results of inner hole detection - (홍삼 내공검출을 위한 X-선 영상처리기술 (II) - 내공검출결과 -)

  • 손재룡;최규홍;이강진;최동수;김기영
    • Journal of Biosystems Engineering
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    • v.28 no.1
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    • pp.45-52
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    • 2003
  • Red ginsengs are inspected manually by examining those in the dark room with back light illumination. Manual inspection is often influenced by physical condition of inspectors. Sometimes. the best grade, heaven. has some inner holes though it was inspected by a specialist. In order to resolve this problem, this study was performed to develop image processing algorithm to detect the inner holes in the x-ray image of ginseng. Because of little gray value difference between background and ginseng in the image. simple thresholding method was not appropriate. Modified watershed algorithm was used to differentiate the inner holes from background and normal ginseng body. Inner hole edge region detected by watershed algorithm consists of many number of blobs including normal portions. With line profile analysis with scanning one line at a time beginning the starting point. it shelved two peaks both ends representing extracting each blobs. in which setting threshold value as of lower peak value enabled us to obtain inner hole image. Once this procedure has to be done till the finishing point it is completing inner hole detection for one blob. Thus. conducting ail blobs by this procedure is completing inner detection of one whole ginseng. Detection results of the inner holes fer various size of red ginsengs were good even though there was small detection variation. 6.2%. according to position of x-rat tube.

Technique of Seam-Line Extraction for Automatic Image Mosaic Generation (자동 모자이크 영상제작을 위한 접합선 추출기법에 관한 연구)

  • Song, Nak-Hyeon;Lee, Sung-Hun;Oh, Kum-Hui;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.1
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    • pp.47-53
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    • 2007
  • Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

Performance Analysis of Adaptive Corner Shrinking Algorithm for Decimating the Document Image (문서 영상 축소를 위한 적응형 코너 축소 알고리즘의 성능 분석)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.4 no.2
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    • pp.211-221
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    • 2003
  • The objective of this paper is performance analysis of the digital document image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element. In this paper, the performance comparison of proposed method and conventional methods in terms of subjective performance and hardware complexity is analyzed and the preferable approach for developing the decimation algorithm of the digital document image on the basis of this analysis result has been reviewed.

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An FPGA-based Parallel Hardware Architecture for Real-time Eye Detection

  • Kim, Dong-Kyun;Jung, Jun-Hee;Nguyen, Thuy Tuong;Kim, Dai-Jin;Kim, Mun-Sang;Kwon, Key-Ho;Jeon, Jae-Wook
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.12 no.2
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    • pp.150-161
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    • 2012
  • Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.

Luminance Stabilization of Image Sequence (영상 시퀀스의 밝기변화 보정)

  • Lee, Im-Geun;Han, Soow-Han
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.7
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    • pp.1661-1666
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    • 2010
  • Due to light condition or shadow around camera, acquired image sequence is often degraded by intensity fluctuation. This artifact is called luminance flicker. As the luminance flicker corrupts the performance of motion estimation or object detection, it should be corrected before further processing. In this paper, we analyze the flicker generation model and propose the new algorithm for flicker reduction. The proposed algorithm considers gain and offset parameter separately, and stabilizes the luminance fluctuation based on these parameters. We show the performance of the proposed method by testing on the sequence with artificially added luminance flicker and real sequence with object motion.

Fragile Watermarking Based on LBP for Blind Tamper Detection in Images

  • Zhang, Heng;Wang, Chengyou;Zhou, Xiao
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.385-399
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    • 2017
  • Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

Tumor Detection Algorithm by using Mammogram Image Processing (맘모그램 영상처리를 이용한 종양검출 알고리즘)

  • Song, Kyohyuk;Chon, Minhee;Joo, Wonjong;Kim, Gibom
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.3_1spc
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    • pp.496-503
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    • 2013
  • Recently, the death rate owing to breast cancers has been increasing, and the occurrence age for breast cancers is lowering every year. Mammography is known to be a reliable detection method for breast cancers and works by detecting texture changes, calcifications, and other potential symptoms. In this research on breast cancer detection, candidate objects were detected by using image processing on mammograms, and feature analysis was used to classify candidate objects as benign tumors and malignant tumors. To find candidate objects, image pre-processing and binarization using multiple thresholds, and the grouping of micro-calcifications were used. More than 50 shape features and intensity features were used in the classification. The performance of the detection algorithm by using Euclidian distance method for benign tumors was 93%, and the classification error rate was approximately 2%.

The Development for Vision-Based Realtime Speed Measuring Algorithm (영상처리를 이용한 여행시간 및 속도 계측 알고리즘의 개발)

  • 오영태;조형기;정의환
    • Journal of Korean Society of Transportation
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    • v.14 no.4
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    • pp.107-129
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    • 1996
  • Recently, surveillance system designed to collect various trsffic information are becoming new areas of development . Among these, the image detector is a ayatem which can measure the travel time and speed in realtime and this is emerging as the most effcient tool to be available in future related areas. But in measuring wide-area information in realtime, the image detector are yet full of problem in its accuracy. The aim of this ahesis is to develop an algorithms which can collect wide-area information such as travel time and travel speed in urban networks and freeways in realtime. The information on wide-area such as travel time and travel speed is important in accomplishing strategic function in traffic control. The algorithm developed from this study is based on the image tracking model which tracks a moving vehicle form image datas collected continuously, and is constructed to perform realtime measurement. To evaluate the performance of the developed algorithms, 600 ind vidual vehicles in total were used as data for the study, and this evaluation was carried out with the differenciation of day and night condition at the access roads in front of AJou University, In the statistical analysis results, the error rate was recorded as 5.69% and it has proved to be applicable on the field in both day and noght conditions.

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