• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.2
• /
• pp.281-288
• /
• 2009

In the paper, we try to develop the methodology for updating road networks of large-scale digital maps by using construction drawing data. For the purpose, it is pre-requite step to merge road networks detached in CAD drawing data. As such, tie points are identified in neighboring drawings and used for solving the parameters of 2D conformal transformation between drawings. Then, the merged road network in CAD data is transformed to the coordinate system of digital maps. In the process, IPs in the drawings are considered as control information and 2D affine transformation is selected for coordinate transformation. Through the experiments with real dataset, we can identify that the developed method is valid and generally applicable.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2138-2144
• /
• 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 Korea Multimedia Society
• /
• v.15 no.1
• /
• pp.63-70
• /
• 2012

In this paper an extension to an original active shape model(ASM) for facial feature extraction is presented. The original ASM suffers from poor shape alignment by aligning the shape model to a new instant of the object in a given image using a simple similarity transformation. It exploits only informations such as scale, rotation and shift in horizontal and vertical directions, which does not cope effectively with the complex pose variation. To solve the problem, new shape alignment with 6 degrees of freedom is derived, which corresponds to an affine transformation. Another extension is to speed up the calculation of the Mahalanobis distance for 2-D profiles by trimming the profile covariance matrices. Extensive experiment is conducted with several images of varying poses to check the performance of the proposed method to segment the human faces.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.1
• /
• pp.104-110
• /
• 2009

In this paper, we suggest a new technique which employ the pipelined architecture for the implementation of the SAP adaptive filter using variable step size. According as SAP adaptive filter is sufficiently decomposed, a simplified SAP adaptive filter can be derived, and the weights of adaptive sub-filters can be updated by a simple formular without a matrix inversion. The convergence speed and the steady state error of the simplified SAP adaptive filter are improved by using variable step size. For practical implementation, the simplified SAP adaptive sub-filters are transformed by the pipeline technique.

• The Transactions of the Korea Information Processing Society
• /
• v.2 no.5
• /
• pp.691-700
• /
• 1995

Most fractal image codings using fractal concept require long encoding time because a large amount of computation is needed to find an optimal affine transformation point. Such a problem can be solved by designing a block classifier fitted to characteristics of image blocks. In general, it is possible to predict more precise and various types of blocks in frequency domain than in spatial domain. In this paper, we propose a block classifier to predict the block type using characteristics of DCT(Discrete Cosine Transform). This classifier has merits to enhance the quality of decoded images as well as to reduce the encoding time meeting fractal features. AC coefficient values in frequency domain make it possible to predict various types of blocks. As the results, the number of comparisons between a range block and the correspoding domain blocks to reach an optimal affine transformation point can be reduced. Specially, signs of DCT coefficients help to find the optimal affine transformation point with only two isometric transformations by eliminating unnecessary isometric transformations among eight isometric transformations used in traditional fractal codings.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.2
• /
• pp.883-900
• /
• 2017

In this paper block based blind secure gray image watermarking scheme based on discrete wavelet transform and singular value decomposition is proposed. In devising the proposed scheme, security is given high importance along with other two requirements: robustness and imperceptibility. The use of discrete wavelet transform not only improves robustness but the selection of bands with high tolerance towards noise caused an improvement in terms of imperceptibility. The robustness further improved due to the involvement of singular vectors along with singular values in watermark embedding and extraction process. Finally, to achieve security, the selected DWT band is decomposed into smaller blocks and random blocks are chosen for modification. Furthermore, the elements of left and right singular vectors of selected blocks are chosen based on their dependence upon each other for watermark embedding. Various experiments using different images as host and watermark were conducted to examine and validate the proposed technique. Additionally, the proposed technique is tested against various attacks like compression, affine transformation, cropping, translation, X shearing, scaling, Y shearing, filtering, blurring, different kinds of noises, histogram equalization, rotation, etc. Lastly, the proposed technique is compared with state-of-the-art watermarking techniques and their comparison shows significant improvement of proposed scheme over existing techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.5
• /
• pp.407-414
• /
• 2015

Interest points are generally located at the pixels where height changes occur. So, interest points can be the significant pixels for DSM generation, and these have the important role to generate accurate and reliable matching results. Manual operation is widely used to extract the interest points and to match stereo satellite images using these for generating height information, but it causes economic and time consuming problems. Thus, a tie point extraction method using Harris-affine technique and SIFT(Scale Invariant Feature Transform) descriptors was suggested to analyze height information of buildings in this study. Interest points on buildings were extracted by Harris-affine technique, and tie points were collected efficiently by SIFT descriptors, which is invariant for scale. Searching window for each interest points was used, and direction of tie points pairs were considered for more efficient tie point extraction method. Tie point pairs estimated by proposed method was used to analyze height information of buildings. The result had RMSE values less than 2m comparing to the height information estimated by manual method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.4A
• /
• pp.291-300
• /
• 2002

In this paper, a way of constituting optimized S box and G function was suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over GF(2$\^$8/) which has neither a fixed point, whose input and output are the same except 0 and 1, nor an opposite flexed number, whose output is one's complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes diffusive linear transform with 4 S-box outputs using the matrix of 4$\times$4 over GF(2$\^$8/). G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, there can be no weak input, where a fried point, an opposite fried point, and output can be two's complement of input, and the construction of hardware can be made easy. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.

• Journal of the Korea Computer Industry Society
• /
• v.4 no.4
• /
• pp.589-598
• /
• 2003

In the conventional fractal image compression in the DWT(discrete wavelet transform), the domain and range blocks were classified as B${\times}$B block size first before all domain block for each range block was searched. The conventional method has a disadvantages that the encoding time takes too long, since the domain block for entire image was searched. As an enhancement to such inefficiencies and image quality, this paper proposes wavelet-based fractal image compression with multiscale factors. Thus, this proposed method uses multiscale factor along each level and band to enhance an overall image quality. In encoding process of this method, the range blocks are not searched for all the domain blocks; however, using the self affine system the range blocks are selected from the blocks in the upper level. The image qualify of the conventional method is 32.30[dB], and the proposed method is 35.97[dB]. The image quality is increased by 3.67[dB].

• Journal of Internet Computing and Services
• /
• v.10 no.4
• /
• pp.13-23
• /
• 2009

In this paper we propose an approach for localizing objects in satellite images. Our method exploits matching features based on description vectors. We applied Scale Invariant Feature Transform (SIFT) to object localization. First, we find keypoints of the satellite images and the objects and generate description vectors of the keypoints. Next, we calculate the similarity between description vectors, and obtain matched keypoints. Finally, we weight the adjacent pixels to the keypoints and determine the location of the matched object. The experiments of object localization by using SIFT show good results on various scale and affine transformed images. In this paper the proposed methods use Google Earth satellite images.