• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.231-238
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• 1995

Tc-99m-MIBI (Sestamibi) myocardial SPECT along with TI-201 tomographic Imaging has demonstrated wide application and high image quality sufficient for the diagnosis of myocardial perfusion defect, which consequently reflects regional myocardial blood flow. The qualitative values of myocardial SPECT with Tc-99m-MIBI as well ds the quantitative cases depend in some degree on the reconstruction techniques of multiple projections. Filtered backprojection (FBP) Is the common standard method for reconstruction rather than the complicated and time-consuming arithmetic methods. In FBP it is known that the distribution of radioactivity in reconstructed transverse slices varies with the selected litter parameters such as cutoff frequencies and order (Butterworth case) The cutoff frequencies used in clinicAl practice partially remove and decrease the true radioactive distribution and alter the pixel counts, which lead to underestimation of true counts in specific myocardial regions. In this study, we have investigated the effect of cutoff frequencies of reconstruction filter on the artifactually induced perfusion defects, which are often demonstrated near inferior and/or inferoseptal cardiac walls due to the intense hepatic uptake of Tc-99m-MIBI. A computerized method for Identifying the relative degree of artifactual perfusion defect and for comparing those degrees along with the relative amount of hepatic uptake to myocardium was developed and patient images were studied to observe the quantitative degree of underestimation of myocardial perfusion, and to propose some reasonable threshold of cutoff frequency in the diagnosis of perfusion defect quantitatively. We concluded that from the quantitative viewpoint cutoff frequencies may be used as high as possible with the sacrifice of homogeneity of image quality, and those frequencies lower than the common 0.3 Wyquist frequency would reveal severe degradation of radioactive distribution near inferior and/or inferoseptal myocardium when applying Butterworth or low pass filter.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1145-1156
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• 2002

A method to measure the speed and distance of moving object is proposed using the stereo vision system. One of the most important factors for measuring the speed and distance of moving object is the accuracy of object tracking. Accordingly, the background image algorithm is adopted to track the rapidly moving object and the local opening operator algorithm is used to remove the shadow and noise of object. The extraction efficiency of moving object is improved by using the adaptive threshold algorithm independent to variation of brightness. Since the left and right central points are compensated, the more exact speed and distance of object can be measured. Using the background image algorithm and local opening operator algorithm, the computational processes are reduced and it is possible to achieve the real-time processing of the speed and distance of moving object. The simulation results show that background image algorithm can track the moving object more rapidly than any other algorithm. The application of adaptive threshold algorithm improved the extraction efficiency of the target by reducing the candidate areas. Since the central point of the target is compensated by using the binocular parallax, the error of measurement for the speed and distance of moving object is reduced. The error rate of measurement for the distance from the stereo camera to moving object and for the speed of moving object are 2.68% and 3.32%, respectively.

• Journal of radiological science and technology
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• v.26 no.2
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• pp.63-69
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• 2003

Filtering is necessary to reduce statistical noise and to increase image quality in SPECT images. Noises controled by low-pass filter designed to suppress high spatial frequency in SPECT image. Most SPECT filter function control the degree of high frequency supression by chosing a cut of frequency. The location of cut off frequency determines the affect image noise and spatial resolution. If select the low cut off frequency, its provide good noise suppression but insufficient image quantity and high cut off frequencies increase the image resolution but insufficient noise suppression. The purpose of this study was to determines the optimam cut off level with comparison of FWHM according to cut off level in each kiters-Band-limited, Sheep-logan, Sheep-logan Hanning, Generalized Hamming, Low pass cosine, Parazen and Butterworth filter in SPECT camera. We recorded image along the X, Y, Z-axis with $^{99m}TcO_4$ point source and measured FWHM by use profile curve. We find averaged length is $9.16\;mm{\sim}18.14\;mm$ of FWHM in X, Y, and Z-axis, and Band-limited and Generalized Hamming filters measures 9.16 mm at 0.7 cycle/pixel cut off frequency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.518-523
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• 2017

This paper proposes a novel denoising method based on non-local(NL) means. The NL-means algorithm is effective for removing an additive Gaussian noise, but the denoising parameter should be controlled depending on the noise level for proper noise elimination. Therefore, the proposed method optimizes the denoising parameter according to the noise levels. The proposed method consists of two processes: off-line and on-line. In the off-line process, the relations between the noise level and the denoising parameter of the NL-means filter are analyzed. For a given noise level, the various denoising parameters are applied to the NL-means algorithm, and then the qualities of resulting images are quantified using a structural similarity index(SSIM). The parameter with the highest SSIM is chosen as the optimal denoising parameter for the given noise level. In the on-line process, we estimate the noise level for a given noisy image and select the optimal denoising parameter according to the estimated noise level. Finally, NL-means filtering is performed using the selected denoising parameter. As shown in the experimental results, the proposed method accurately estimated the noise level and effectively eliminated noise for various noise levels. The accuracy of noise estimation is 90.0% and the highest Peak Signal-to-noise ratio(PSNR), SSIM value.

• Journal of radiological science and technology
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• v.31 no.3
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• pp.223-228
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• 2008

The most critical point in the medical use of radiation is to minimize the patient's entrance dose while maintaining the diagnostic function. Low-energy photons (long wave X-ray) among diagnostic X-rays are unnecessary because they are mostly absorbed and contribute the increase of patient's entrance dose. The most effective method to eliminate the low-energy photons is to use the filtering plate. The experiments were performed by observing the image quality. The skin entrance dose was 0.3 mmCu (copper) filter. A total of 80 images were prepared as two sets of 40 cuts. In the first set (of 40 cuts), 20 cuts were prepared for the non-filter set and another 20 cuts for the Cu filter of signal + noise image set. In the second set of 40 cuts, 20 cuts were prepared for the non-filter set and another 20 cuts for the Cu filter of non-signal image (noisy image) with random location of diameter 4 mm and 3 mm thickness of acryl disc for ROC signal at the chest phantom. P(S/s) and P(S/n) were calculated and the ROC curve was described in terms of sensitivity and specificity. Accuracy were evaluated after reading by five radiologists. The number of optically observable lesions was counted through ANSI chest phantom and contrast-detail phantom by recommendation of AAPM when non-filter or Cu filter was used, and the skin entrance dose was also measured for both conditions. As the result of the study, when the Cu filter was applied, favorable outcomes were observed on, the ROC Curve was located on the upper left area, sensitivity, accuracy and the number of CD phantom lesions were reasonable. Furthermore, if skin entrance dose was reduced, the use of additional filtration may be required to be considered in many other cases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.378-387
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• 2003

Digital watermarking is the technique that embeds invisible signalsincluding owner identification information, specific code, or pattern into multimedia data such as image, video and audio. Watermarking techniques can be classified into two groups; robust watermarking and fragile(semi-fragile) watermarking. The main purpose of the robust watermarking is the protection of copyright, whereas fragile(semi-fragile) watermarking prevents image or video data from illegal modifications. To achieve this goal watermark should survive from unintentional modifications such as random noise or compression, but it should be fragile for malicious manipulations. In this paper, an invertible semi-fragile watermarkingalgorithm for authentication and detection of manipulated location in MPEG-2 bit-stream is proposed. The proposed algorithm embeds two kinds of watermarks, which are embedded into quantized DCT coefficients. So it can be applied directly to the compressed bit-stream. The first watermark is used for authentication of video data. The second one is used for detection of malicious manipulations. It can distinguish transcodingin bit-stream domain from malicious manipulation and detect the block-wise locations of manipulations in video data. Also, since the proposed algorithm has an invertible property, recovering original video data is possible if the watermarked video is authentic.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.116-128
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• 2011

In this paper, we propose the structure of a high-performance face-detection engine that responds well to facial rotating changes using rotation transformation which minimize the required memory usage compared to the previous face-detection engine. The validity of the proposed structure has been verified through the implementation of FPGA. For high performance face detection, the MCT (Modified Census Transform) method, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. And the rotation transformation method was added to maintain effectiveness against face rotating changes. The proposed hardware structure was composed of Color Space Converter, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT(Modified Census Transform), Candidate Detector / Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor / Color Overlay Processor. The face detection engine was tested using a Virtex5 LX330 FPGA board, a QVGA grade CMOS camera, and an LCD Display. It was verified that the engine demonstrated excellent performance in diverse real life environments and in a face detection standard database. As a result, a high performance real time face detection engine that can conduct real time processing at speeds of at least 60 frames per second, which is effective against lighting changes and face rotating changes and can detect 32 faces in diverse sizes simultaneously, was developed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.94-104
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• 2007

Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.793-800
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• 2004

In this paper, we propose a new automatic pipe grading algorithm for an efficient management of transmission pipe under the ground. Since the conventional transmission pipe evaluation was conducted by subjective decision made by an individual operator, it was difficult to grade them by means of numerical methods and also hard to realistically construct numerical database system. To solve these problems, we Int obtain some information on the current condition of pipes' sections by shooting laser beam at a regular rate and then apply grading algorithm after complete calculation of minimum diameter of pipe. We use some of preprocessing techniques to reduce noise and also use various color models to consider special conditions of each inner pipe. The measurement of pipes' minimum diameter and decision of grade are performed through a detailed processing stages. By some experimental results performed in the field, we show that over 90 percent of correct grade decisions are made by the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4508-4515
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• 2014

Real-time body detection has been researched actively. On the other hand, the detection rate of color distorted images is low because most existing detection methods use static skin color model. Therefore, this paper proposes a new method for detecting the skin color region using a gradient map and saturation features. The basic procedure of the proposed method sequentially consists of creating a gradient map, extracting a gradient feature of skin regions, noise removal using the saturation features of skin, creating a cluster for extraction regions, detecting skin regions using cluster information, and verifying the results. This method uses features other than the color to strengthen skin detection not affected by light, race, age, individual features, etc. The results of the detection rate showed that the proposed method is 10% or more higher than the traditional methods.