• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2138-2144
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• 2015

Multimodal dual camera system has a stereo-like configuration equipped with an infrared thermal and optical camera. This paper presents stereo calibration methods on multimodal dual camera system using a target board that can be recognized by both thermal and optical camera. While a typical stereo calibration method usually performed with extracted intrinsic and extrinsic camera parameter, consecutive image processing steps were applied in this paper as follows. Firstly, the corner points were detected from the two images, and then the pixel error rate, the size difference, the rotation degree between the two images were calculated by using the pixel coordinates of detected corner points. Secondly, calibration was performed with the calculated values via affine transform. Lastly, result image was reconstructed with mapping regions on calibrated image.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.106-118
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• 2009

Satellite imagery with high resolution of about one meter is used widely in commerce and government applications ranging from earth observation and monitoring to national digital mapping. Due to the expensiveness of IKONOS Pro and Precision products, it is attractive to use the low-cost IKONOS Geo product with vendor-provided rational polynomial coefficients (RPCs), to produce highly accurate mapping products. The imaging geometry of IKONOS high-resolution imagery is described by RFs instead of rigorous sensor models. This paper presents four different polynomial models, that are the offset model, the scale and offset model, the Affine model, and the 2nd-order polynomial model, defined respectively in object space and image space to improve the accuracies of the RF-derived ground coordinates. Not only the algorithm for RF-based ground coordinates but also the algorithm for accuracy improvement of RF-based ground coordinates are developed which is based on the four models, The experiment also evaluates the effect of different cartographic parameters such as the number, configuration, and accuracy of ground control points on the accuracy of geopositioning. As the result of a experimental application, the root mean square errors of three dimensional ground coordinates which are first derived by vendor-provided Rational Function models were averagely 8.035m in X, 10.020m in Y and 13.318m in Z direction. After applying polynomial correction algorithm, those errors were dramatically decreased to averagely 2.791m in X, 2.520m in Y and 1.441m in Z. That is, accuracy was greatly improved by 65% in planmetry and 89% in vertical direction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.834-841
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• 2004

There can be lips transformed geometrically in the lip images according to the location or the pose of camera and speaker. This transformation of the lip images changes geometric information of original lip phases. Therefore, for enhancing global lip information by using partial information of lips to correct lip phases transformed geometrically, in this paper we propose a method that can geometrically correct lips. The method is composed of two steps - the feature-deciding step and the correcting step. In the former, it is for us to extract key points and features of source image according to the its lip model and to create that of target image according to the its lip model. In the latter, we decide mapping relation after partition a source and target image based on information extracted in the previous step into each 4 regions. and then, after mapping, we unite corrected sub-images to a result image. As experiment image, we use fames that contain pronunciation on short vowels of the Korean language and use lip symmetry for evaluating the proposed algorithm. In experiment result, the correcting rate of the lower lip than the upper lip and that of lips moving largely than little was highly enhanced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.313-315
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• 2010

In this paper, we describe research results of developing hardware rasterizer that is applicable to mobile 3D graphics system, designed in SIMD architecture and verified in FPGA. Tile-based scan conversion unit is designed like SIMD architecture running four tiles simultaneously and each tile traverses pixels hierarchical in 3-level so that visiting counts is minimized. As experimental results, $8{\times}8$ is the most efficient size of tile and the last step of tile traversing is performed on $2{\times}2$ sized subtile. The rasterizer supports flat shading and gouraud shading and texture mapper supports affine mapping and perspective corrected mapping. Also, texture mapper supports point sampling mode and bilinear interpolating sampling mode and two types of wrapping modes and various blending modes. The rasterzer operates as 120Mhz on xilinx vertex4 $l{\times}100$ device. To easy verification, texture memory and frame buffer are generated as block rom and block ram.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.41-47
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• 2002

Fractal image compression can reduce the size of image data by the contractive mapping that is affine transformation to find the block(called as range block) which is the most similar to the original image. Even though fractal image compression is regarded as an efficient way to reduce the data size, it has high distortion rate and requires long encoding time. In this paper, we presented a hybrid fractal image compression system with the modified SOFM Vector Quantizer which uses improved competitive learning method. The simulation results showed that the VQ hybrid fractal using improved competitive loaming SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.