• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.402-410
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• 2006

This paper presents a method for feature based block motion estimation that uses multi -resolution image sequences to obtain the panoramic images in the continuous ultrasound image sequences. In the conventional block motion estimation method, the centers of motion estimation blocks are set at the predetermined and equally spaced locations. This requires the large blocks to include at least one feature, which inevitably requires long estimation time. In this paper, we propose an adaptive method which locates the center of the motion estimation blocks at the feature points. This make it possible to reduce the block size while keeping the motion estimation accuracy The Harris-Stephen corner detector is used to get the feature points. The comer points tend to group together, which cause the error in the global motion estimation. In order to distribute the feature points as evenly as Possible, the image is firstly divided into regular subregions, and a strongest corner point is selected as a feature in each subregion. The ultrasound Images contain speckle patterns and noise. In order to reduce the noise artifact and reduce the computational time, the proposed method use the multi-resolution image sequences. The first algorithm estimates the motion in the smoothed low resolution image, and the estimated motion is prolongated to the next higher resolution image. By this way the size of search region can be reduced in the higher resolution image. Experiments were performed on three types of ultrasound image sequences. These were shown that the proposed method reduces both the computational time (from 77ms to 44ms) and the displaced frame difference (from 66.02 to 58.08).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.78-86
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• 2013

In this paper, we propose design of a high-performance vehicle imaging information system for an efficient vehicle imaging stabilization. The proposed system was designed the algorithm by divided as motion estimation and motion compensation. The motion estimation were configured as local motion vector estimation and irregular local motion vector detection, global motion vector estimation. The motion compensation was corrected for the four directions for compensate to the shake of vehicle video image using estimate GMV. The designed algorithm were designed the motion compensation technology chip by applied to IP for vehicle imaging stabilization. In this paper, the experimental results of the proposed vehicle imaging information system were proved to the effectiveness by compared with other methods, because imaging stabilization of moving vehicle was not used of memory by processing real-time. Also, it could be obtained to reduction effect of calculation time by arithmetic operation through to block matching.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1052-1061
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• 2018

In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4438-4460
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• 2017

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.512-522
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• 2005

In this paper an algorithm of image alignments for constructing seamless mosaics is proposed. After the global alignment has been run, there may still be localized mis-registrations present in the mosaic. Due to mis-registrations, there may be seams in the mosaic, such as breaking, blurring, and doubling of lines. To solve this problem, we need an algorithm of residual motion estimation, which minimizes mis-registrations. In the conventional algorithms of residual motion estimation, computational powers are too heavy and estimators of camera parameters are additionally needed such as focal lengths. In the proposed algorithm, residual motion vectors are estimated with the adequate size of estimation and measurement windows and with adjustment of initial vectors according to the established priority. By construction of mosaics with the proposed algorithm, we demonstrate the removal of seams by mis-registrations.

• The Journal of Information Technology
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• v.7 no.2
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• pp.93-104
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• 2004

Sports scene is characterized by large amount of global motion due to pan and zoom of camera motion, and includes many small objects moving independently. Some short period of sports games is thrilling to televiewers, and important to producers. At the same time that kinds of scenes exhibit exceptionally dynamic motions and it is very difficult to analyze the motions with conventional algorithms. In this thesis, several algorithms are proposed for global motion analysis on these dynamic scenes. It is shown that proposed algorithms worked well for motion compensation and panorama synthesis. When cascading the inter frame motions, accumulated errors are unavoidable. In order to minimize these errors, interpolation method of motion vectors is introduced. Affined transform or perspective projection transform is regarded as a square matrix, which can be factorized into small amount of motion vectors. To solve factorization problem, we preposed the adaptation of Newton Raphson method into vector and matrix form, which is also computationally efficient. Combining multi frame motion estimation and the corresponding interpolation in hierarchical manner enhancement algorithm of motion parameters is proposed, which is suitable for motion compensation and panorama synthesis. The proposed algorithms are suitable for special effect rendering for broadcast system, video indexing, tracking in complex scenes, and other fields requiring global motion estimation.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.6
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• pp.529-535
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• 2016

This study focuses on the comparison of measured data from 6-DOF motion sensor and strain gauge installed in the IBRV ARAON during 2015 summer voyage in the Arctic. Procedures to calculate the global ice load from MotionPak II inertial measurement system and the local load from stain gauge system are discussed. The ship's speed and peak load are determined in the concept of an ice collision "event". It is found that the peak values in the global ice calculated form whole ship motion analysis fall in the range of 1.5~3 times of the local ice load based in strain gauge measurement.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.77-85
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• 2018

This paper proposes a robust digital video stabilization algorithm to extract and track an object, which uses a phase correlation-based motion correction. The proposed video stabilization algorithm consists of background stabilization based on motion estimation and extraction of a moving object. The motion vectors can be estimated by calculating the phase correlation of a series of frames in the eight sub-images, which are located in the corner of the video. The global motion vector can be estimated and the image can be compensated by using the multiple local motions of sub-images. Through the calculations of the phase correlation, the motion of the background can be subtracted from the former frame and the compensated frame, which share the same background. The moving objects in the video can also be extracted. In this paper, calculating the phase correlation to track the robust motion vectors results in the compensation of vibrations, such as movement, rotation, expansion and the downsize of videos from all directions of the sub-images. Experimental results show that the proposed digital image stabilization algorithm can provide continuously stabilized videos and tracking object movements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.164-173
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• 2013

In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.363-371
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• 2014

In this paper, a new super-resolution algorithm is proposed by using successive frames for generating high-resolution frames with better quality than those generated by other conventional interpolation methods. Generally, each frame used for super-resolution must only have global translation and motions of sub-pixel unit to generate good result. However, the newly proposed MSR algorithm in this paper is exempt from such constraints. The proposed algorithm consists of three main processes; motion estimation for image registration, normalization of motion vectors, and pattern analysis of edges. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.