• Journal of the Korea Society of Computer and Information
• /
• v.10 no.4 s.36
• /
• pp.191-201
• /
• 2005

In this paper, we propose a method to calculate camera motion parameter, which is based on efficient invariant features irrelevant to the camera veiwpoint. As feature information in previous research is variant to camera viewpoint. information content is increased, therefore, extraction of accurate features is difficult. LM(Levenberg-Marquardt) method for camera extrinsic parameter converges on the goat value exactly, but it has also drawback to take long time because of minimization process by small step size. Therefore, in this paper, we propose the extracting method of invariant features to camera viewpoint and two-stage calculation method of camera motion parameter which enhances accuracy and convergent degree by using camera motion parameter by 2D homography to the initial value of LM method. The proposed method are composed of features extraction stage, matching stage and calculation stage of motion parameter. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.46 no.6
• /
• pp.65-72
• /
• 2009

This paper presents a vision based localization method for indoor mobile robots using the types of vertices from a monocular image. In the images captured from a camera of a robot, the types of vertices are determined by searching vertical edges and their branch edges with a geometric constraints. For obtaining correspondence between the comers of a 2-D map and the vertex of images, the type of vertices and geometrical constraints induced from a geometric analysis. The vertices are matched with the comers by a heuristic method using the type and position of the vertices and the comers. With the matched pairs, nonlinear equations derived from the perspective and rigid transformations are produced. The pose of the robot is computed by solving the equations using a least-squares optimization technique. Experimental results show that the proposed localization method is effective and applicable to the localization of indoor environments.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.5
• /
• pp.55-63
• /
• 2011

This paper describes new moving target detection technique combining two algorithms to detect targets and reject clutters in video frame images for surveillance system: One obtains the region of moving target using phase correlation method using $N{\times}M$ sub-block images in frequency domain. The other uses adaptive threshold using learning weight for extracting target candidates in subtracted image. The block region with moving target can be obtained using the characteristics that the highest value of phase correlation depends on the movement of largest image in block. This technique can be used in camera motion environment calculating and compensating camera movement using FFT phase correlation between input video frame images. The experimental results show that the proposed algorithm accurately detects target(s) with a low false alarm rate in variety environment using the receiver operating characteristics (ROC) curve.

• Journal of Biomedical Engineering Research
• /
• v.25 no.6
• /
• pp.537-543
• /
• 2004

In order to create three-dimensional model for human body, a method that reconstructs geometric models from contour lines on cross-section images is commonly used. We can get a set of contour lines by acquiring CT or MR images and segmenting anatomical structures. Previously proposed method divides entire contour line into simply matched regions and clefts. Since long processing time is required for reconstructing cleft regions, its performance might be degraded when manipulating complex data such as cross-sections for human body. In this paper, we propose a fast reconstruction method. It generates a triangle strip with single tiling operation for simple region that does not contain branch structures. If there exist branches in contour lines, it partitions the contour line into several sub-contours by considering the number of vertices and their spatial distribution. We implemented an automatic surface reconstruction system by using our method which reconstructs three-dimensional models for anatomical structures.

• Journal of Biomedical Engineering Research
• /
• v.18 no.3
• /
• pp.223-231
• /
• 1997

In this paper, an interframe coding method for volumetric medical images is proposed. By treating interslice variations as the motion of bones or tissues, we use the motion compensation (MC) technique to predict the current frame from the previous frame. Instead of a block matching algorithm (BMA), which is the most common motion estimation (ME) algorithm in video coding, image warping with biolinear transformation has been suggested to predict complex interslice object variation in medical images. When an object disappears between slices, however, warping prediction has poor performance. In order to overcome this drawback, an overlapped block motion compensation (OBMC) technique is combined with carping prediction. Motion compensated residual images are then encoded by using an embedded zerotree wavelet (EZW) coder with small modification for consistent quality of reconstructed images. The experimental results show that the interframe coding suing warping prediction provides better performance compared with interframe coding, and the OBMC scheme gives some additional improvement over the warping-only MC method.

• Journal of Intelligence and Information Systems
• /
• v.8 no.2
• /
• pp.1-13
• /
• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• Journal of Satellite, Information and Communications
• /
• v.9 no.2
• /
• pp.33-37
• /
• 2014

This paper propose a method to sort flame regions and non-flame regions in a color image based on temperature Characteristics of flame. The traditional algorithms simply detect flame regions those are colored between yellow and red and there are lot of false detection in this method. But the colors of real flame are fallen between white and red and flame color variation over the flame. In this paper, it reduce false detection by separating colors according to temperature Characteristics of flame. The proposed method firstly finds a color model to express the temperature Characteristics of fire and then the color model is non-linearly quantized based on color values and analyzed using histogram and finally detect the candidate flame regions. The proposed method has 71.8% of matching rate and if it is compared with non-matching rate of traditional algorithms, the non-matching rate is improved by 27 times than others.

• The KIPS Transactions:PartB
• /
• v.15B no.1
• /
• pp.9-16
• /
• 2008

In this paper, we present an algorithm for synthesizing intermediate view image from a stereoscopic pair of images. An image of multiview is need for people in order to easily recognize 3D image. However, if many cameras are use for that, not only does system get more complicated but also transmission rating cause a big trouble. Hence, stereo images are photograph and issue on the sending side and algorithm to generate several intermediate view image is able to be use on the receiving side. The proposed method is based on disparity space image. First of all, disparity space image that is depicted by the gap of pixel followed by disparity of stereo image is generated. Disparity map is made by utilizing disparity space image for searching for optimal disparity path then eventual intermediate view image is generated after occlusion region which does not match is processed. Experimental results illustrate the performance of the proposed technique and we obtained a high quality image of more than 30 dB PSNR.

• Journal of Internet Computing and Services
• /
• v.4 no.4
• /
• pp.9-14
• /
• 2003

A GUI (graphical user interface) has been a dominant platform for HCI (human computer interaction). A GUI - based interaction has made computers simpler and easier to use. The GUI - based interaction, however, does not easily support the range of interaction necessary to meet users' needs that are natural. intuitive, and adaptive. In this paper, the modified BMA (block matching algorithm) is proposed to track a hand in a sequence of an image and to recognize it in each video frame in order to replace a mouse with a pointing device for a virtual reality. The HCI system with 30 frames per second is realized in this paper. The modified BMA is proposed to estimate a position of the hand and segmentation with an orientation of motion and a color distribution of the hand region for real - time processing. The experimental result shows that the modified BMA with the YCbCr (luminance Y, component blue, component red) color coordinate guarantees the real - time processing and the recognition rate. The hand tracking by the modified BMA can be applied to a virtual reclity or a game or an HCI system for the disable.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.727-736
• /
• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.