• Proceedings of the KSME Conference
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• 2003.04a
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• pp.845-850
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• 2003

The scattered light pattern from a machined surface generally contains much information concerning the surface roughness. The light pattern can be acquired by optical system and analyzed by statistical method. This kind of surface roughness measurement system can be easily adopted on the machine measurement. But the fully assembled system is too complex to implement on small systems using micro-controller. This study proposes the idea of reducing the number of optical components by removing screen and examines image processing of a light pattern to minimize the negative result of incomplete optical system. And the Gaussian blur filtering is concluded to be the best method of proposed measurement system. Furthermore light intensity variation of image pattern can be treated as a signal, therefore FIR filtering gives the similar result of Gaussian blur effect.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.703-708
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• 2009

The present paper describes the application of an improved impression transfer vector method (Sakurai et al., 2007) to transform the three basic dimensions (Evaluation, Activity, and Potency) of higher-order impression. First, a set of shapes and surface textures of faces was represented by multi-dimensional vectors. Second, the variation among faces was coded in reduced parameters derived by applying principal component analysis. Third, a facial attribute along a given impression dimension was analyzed to select discriminative parameters from among principal components with higher sensitivity to impressions, and obtain an impression transfer vector. Finally, the parametric coordinates were changed by adding or subtracting the impression transfer vector and the image was manipulated so that its facial appearance clearly exhibits the transformed impression. A psychological rating experiment confirmed that the impression transfer vector modulated three dimensions of higher-order impression. We discussed the versatility of the impression transfer vector method.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1104-1113
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• 2000

This paper proposes an efficient reverse engineering technique for compound surfaces using a boundary detection method. This approach consists in extracting geometric edge information using a vision system, which can be used in order to drastically reduce geometric errors in the vicinity of compound surface boundaries. Through the image-processing technique and the interpolation process, boundaries are reconstructed by either analytic curves (e. g. circle, ellipse, line) or parametric curves (B-spline curve). In other regions, except boundaries, geometric data are acquired on CMM as points inspected using a touch type probe, and then they are interpolated on several surfaces using a B-spline skinning method. Finally, the boundary edge and the skinned surfaces are combined to reconstruct the final compound surface. Through simulations and experimental works, the effectiveness of the proposed method is confirmed.

• Progress in Medical Physics
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• v.21 no.2
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• pp.153-164
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• 2010

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.201-208
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• 2012

Accurately segmenting lumen border in intravascular ultrasound images (IVUS) is very important to study vascular wall architecture for diagnosis of the cardiovascular diseases. After each of IVUS image is transformed to a polar coordinated image, initial points are detected using wavelet transform. Then, lumen border is initialized as the set of important points using non parametric probability density function and smoothing function by removing outlier initial points occurred by noises and artifacts. Finally, polynomial curve fitting is applied to obtain real lumen border using filtered important points. The evaluation of proposed method was performed with related method and the proposed method produced accurate lumen contour detection when compared to another method in most types of IVUS images.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.107-116
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• 2003

This study investigated how appropriate the classification methods based on conventional spectral characteristics are for high resolution imagery. A supervised classification mixing parametric and non-parametric rules, a method in which fuzzy theory is applied to such classification, and an unsupervised method were performed and compared to each other for accuracy. In addition, comparing the result screen-digitized through interpretation to the classification result using spectral characteristics, this study analyzed the conformity of both methods. Although the supervised classification to which fuzzy theory was applied showed the best performance, the application of conventional classification techniques to high resolution imagery had some limitations due to there being too much information unnecessary to classification, shadows, and a lack of spectral information. Consequently, more advanced techniques including integration with other advanced remote sensing technologies, such as lidar, and application of filtering or template techniques, are required to classify land cover/use or to extract useful information from high resolution imagery.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.9-18
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• 2012

The BIM called information modeling is used by tool not only it will simply be appearing the image and can save the information. Recently, there is a lot of case that improves the construction productivity by using the BIM during the life cycle of bridge from order to management. Although we already recognize the advantage of BIM, it is a careful phase to use the BIM. Therefore, We made the BIM for bridge, evaluated the possibility that can build the object used in the civil engineer, studied about the utility, the improvement in order to use the BIM properly. As a result, the BIM can recycle the information by using parametric model and attribute the efficiency and accuracy on drawing and calculating the quantity. The BIM is able to help productivity increase by using the builded model after we spend the effort building a model in early stage.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.95-103
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• 1998

This paper proposes an image segmentation algorithm based on fusion of range and intensity images. Based on Bayesian theory, a priori knowledge is encoded by the Markov random field (MRF). A maximum a posteriori (MAP) estimator is constructed using the features extracted from range and intensity images. Objects are approximated by local planar surfaces in range images, and the parametric space is constructed with the surface parameters estimated pixelwise. In intensity images the ${\alpha}$-trimmed variance constructs the intensity feature. An image is segmented by optimizing the MAP estimator that is constructed using a likelihood function based on edge information. Computer simulation results shw that the proposed fusion algorithm effectively segments the images independentl of shadow, noise, and light-blurring.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.11-18
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• 2016

Magnetic resonance image (MRI) is widely used in brain research field and medical image. Especially, non-invasive brain activation acquired image technique, which is functional magnetic resonance image (fMRI) is used in brain study. In this study, we investigate brain activation occurred by LED light stimulation. For investigate of brain activation in experimental small animal, we used high magnetic field 9.4T MRI. Experimental small animal is Balb/c mouse, method of fMRI is using echo planar image (EPI). EPI method spend more less time than any other MRI method. For this reason, however, EPI data has low contrast. Due to the low contrast, image pre-processing is very hard and inaccuracy. In this study, we planned the study protocol, which is called block design in fMRI research field. The block designed has 8 LED light stimulation session and 8 rest session. All block is consist of 6 EPI images and acquired 1 slice of EPI image is 16 second. During the light session, we occurred LED light stimulation for 1 minutes 36 seconds. During the rest session, we do not occurred light stimulation and remain the light off state for 1 minutes 36 seconds. This session repeat the all over the EPI scan time, so the total spend time of EPI scan has almost 26 minutes. After acquired EPI data, we performed the analysis of this image data. In this study, we analysis of EPI data using statistical parametric map (SPM) software and performed image pre-processing such as realignment, co-registration, normalization, smoothing of EPI data. The pre-processing of fMRI data have to segmented using this software. However this method has 3 different method which is Gaussian nonparametric, warped modulate, and tissue probability map. In this study we performed the this 3 different method and compared how they can change the result of fMRI analysis results. The result of this study show that LED light stimulation was activate superior colliculus region in mouse brain. And the most higher activated value of segmentation method was using tissue probability map. this study may help to improve brain activation study using EPI and SPM analysis.

• Progress in Medical Physics
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• v.15 no.1
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• pp.45-53
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• 2004

SPM has been widely applied for comparison studios of the functional image data among groups of patients or individuals under different conditions and these images are from people ranging from children to adults. However, the analysis of children's brain images by using SPM can make children's brain images normalized to an adult's template image and this can result in some errors. So this study created the children's mean MR images based on the Magnetic Resonance Images of 36 normal children (age: 2～6, average age: 4.36, SD age: 1.41, M/F: 17/19), and the children's mean SPECT images by using SPECT images of 13 normal children (age: 2～6, average age: 4.80, SD age: 1.17, M/F: 10/3). We created the Korean children's brain template image, based on those mean images, and then we compared between the positions of the clusters, based on the blood flow, by normalizing ADHD children's SPECT image to Korean children's template image and SPM adult's template image. As a result of the analysis, the variation of the cluster positions was found to be a maximum of 25 ㎜. Therefore, we should be aware that we need to consider the template image and the p-value when we analyze the chlidren's brain image by using SPM.