• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9A
• /
• pp.1401-1410
• /
• 1999

In this paper, we propose a fast block matching algorithm using the lower and upper bound of mean absolute difference (MAD) which is calculated at the search region overlapped with neighbor blocks. At first, we calculate the lower bound of MAD and reduce the search point by using this lower bound. In this method, we can get good prediction error performance close to full search block matching algorithm (FSBMA), but there exists some computational complexity that has to be reduced. Therefore, we further reduce the computational complexity by using pixel subsampling besides the lower and upper bound of MAD. Experimental results show that we can remarkably reduce the computational complexity with good prediction error performance close to FSBMA.

• The KIPS Transactions:PartB
• /
• v.12B no.5 s.101
• /
• pp.521-526
• /
• 2005

In this Paper, we propose a keyword spotting system as an alternative to searching system for poor quality Korean document images and compare the Proposed system with an OCR-based document retrieval system. The system is composed of character segmentation, feature extraction for the query keyword, and word-to-word matching. In the character segmentation step, we propose an effective method to remove the connectivity between adjacent characters and a character segmentation method by making the variance of character widths minimum. In the query creation step, feature vector for the query is constructed by a combination of a character model by typeface. In the matching step, word-to-word matching is applied base on a character-to-character matching. We demonstrated that the proposed keyword spotting system is more efficient than the OCR-based one to search a keyword on the Korean document images, especially when the quality of documents is quite poor and point size is small.

• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.1
• /
• pp.13-22
• /
• 2009

In this paper, we propose the 3D shape reconstruction method that combine the mosaic method and the active stereo matching using the laser beam. The active stereo matching method detects the position information of the irradiated laser beam on object by analyzing the color and brightness variation of left and right image, and acquires the depth information in epipolar line. The mosaic method extracts feature point of image by using harris comer detection and matches the same keypoint between the sequence of images using the keypoint descriptor index method and infers correlation between the sequence of images. The depth information of the sequence image was calculated by the active stereo matching and the mosaic method. The merged depth information was reconstructed to the 3D shape information by wrapping and blending with image color and texture. The proposed reconstruction method could acquire strong the 3D distance information, and overcome constraint of place and distance etc, by using laser slit beam and stereo camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.2
• /
• pp.75-80
• /
• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• Spatial Information Research
• /
• v.16 no.2
• /
• pp.193-206
• /
• 2008

If stereo images is used for Digital Elevation Model (DEM) generation, a DEM is generally made by matching left image against right image from stereo images. In stereo matching, tie-points are used as initial match candidate points. The number and distribution of tie-points influence the matching result. DEM made from matching result has errors such as holes, peaks, etc. These errors are usually interpolated by neighbored pixel values. In this paper, we propose the DEM generation method combined with automatic tie-points extraction using existing DEM, image pyramid, and interpolating new DEM using existing DEM for more reliable DEM. For test, we used IKONOS, QuickBird, SPOT5 stereo images and a DTED level 2 data. The test results show that the proposed method automatically makes reliable DEMs. For DEM validation, we compared heights of DEM by proposed method with height of existing DTED level 2 data. In comparison result, RMSE was under than 15 m.

• The KIPS Transactions:PartB
• /
• v.15B no.6
• /
• pp.517-526
• /
• 2008

Stereo vision is a fundamental method for measuring 3D structures by observing them from two cameras placed on different positions. In order to reconstruct 3D structures, it is necessary to create a disparity map from a pair of stereo images. To create a disparity map we compute the matching cost for each point correspondence and compute the disparity that minimizes the sum of the whole matching costs. In this paper, we propose a method to estimate a dense disparity map using region segmentation. We segment each scanline using region homogeneity properties. Using the segmented regions, we prohibit false matches in the stereo matching process. Disparities for pixels that failed in matching are filled by interpolating neighborhood disparities. We applied the proposed method to various stereo images of real environments. Experimental results showed that the proposed method is stable and potentially viable in practical applications.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.1 s.45
• /
• pp.57-65
• /
• 2007

In the fast block matching algorithm. search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image qualify. In this paper, we propose a new fast block matching algorithm using the flat-hexagon search pattern that ate solved disadvantages of the diamond pattern search algorithm(DS) and the hexagon-based search algorithm(HEXBS). Our proposed algorithm finds mainly the motion vectors that not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the DS and HEXBS, the proposed f)at-hexagon search algorithm(FHS) improves about $0.4{\sim}21.3%$ in terms of average number of search point per motion vector estimation and improves about $0.009{\sim}0.531dB$ in terms of PSNR(Peak Signal to Noise Ratio).

• Journal of radiological science and technology
• /
• v.43 no.2
• /
• pp.105-114
• /
• 2020

This study aimed to assess of beam-matching accuracy for an 8 MV beam between the same model linear accelerators(Linac) commissioned over two years. Two models were got the customer acceptance procedure(CAP) criteria. For commissioning data for beam-matched linacs, the percentage depth doses(PDDs), beam profiles, output factors, multi-leaf collimator(MLC) leaf transmission factors, and the dosimetric leaf gap(DLG) were compared. In addition, the accuracy of beam matching was verified at phantom and patient levels. At phantom level, the point doses specified in TG-53 and TG-119 were compared to evaluate the accuracy of beam modelling. At patient level, the dose volume histogram(DVH) parameters and the delivery accuracy are evaluated on volumetric modulated arc therapy(VMAT) plan for 40 patients that included 20 lung and 20 brain cases. Ionization depth curve and dose profiles obtained in CAP showed a good level for beam matching between both Linacs. The variations in commissioning beam data, such as PDDs, beam profiles, output factors, TF, and DLG were all less than 1%. For the treatment plans of brain tumor and lung cancer, the average and maximum differences in evaluated DVH parameters for the planning target volume(PTV) and the organs at risk(OARs) were within 0.30% and 1.30%. Furthermore, all gamma passing rates for both beam-matched Linacs were higher than 98% for the 2%/2 mm criteria and 99% for the 2%/3 mm criteria. The overall variations in the beam data, as well as tests at phantom and patient levels remains all within the tolerance (1% difference) of clinical acceptability between beam-matched Linacs. Thus, we found an excellent dosimetric agreement to 8 MV beam characteristics for the same model Linacs.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.1C
• /
• pp.9-15
• /
• 2007

We propose the fast full search algorithm that reduces the computation of the block matching algorithm which is used for motion estimation of the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion pictures. However the proposed method is good for the fast and slow motion because it estimates the motion in the new search order after partitioning the search window. Also, when finding the motion vector, this paper presents the method that reduces the complexity by computing the matching error in the order which is determined by local image complexity. The proposed algorithm reduces the computation up to 99% for block matching error compared with the conventional spiral full search algorithm without any loss of image quality.

• Journal of Advanced Navigation Technology
• /
• v.17 no.3
• /
• pp.306-313
• /
• 2013

In this paper, we implemented the matching system between user-centered ubiquitous virtual reality and the real world for smart home control. Implemented system consists of the smart devices that are equipped with the ubiquitous virtual reality, the hardware for a real-world representation, and the matching software. To communication and data control, we designed the TCP/IP communication protocol, and used the WPAN-based 802.15.4 ZigBee module. The main point of proposed the authoring tool-based ubiquitous virtual reality is the user-centered environment that users can place the objects such as smart TV, home appliances similar to embellish their home structure. Some experiments are conducted so as to verify the proposed model, and as a results, the proposed matching system is well performed.