• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.11
• /
• pp.2754-2768
• /
• 2013

Video fingerprints generated from global features are usually vulnerable against general geometric transformations. In this paper, a novel video fingerprinting algorithm is proposed, in which a new spatio-temporal gradient is designed to represent the spatial and temporal information for each frame, and a new partition scheme, based on concentric circle and rings, is developed to resist the attacks efficiently. The centroids of spatio-temporal gradient orientations (CSTGO) within the circle and rings are then calculated to generate a robust fingerprint. Our experiments with different attacks have demonstrated that the proposed approach outperforms the state-of-the-art methods in terms of robustness and discrimination.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.753-756
• /
• 2000

In this paper we present and compare two different spatio-temporal decorrelation learning algorithms for updating the weights of a linear feedforward network with FIR synapses (MIMO FIR filter). Both standard gradient and the natural gradient are employed to derive the spatio-temporal decorrelation algorithms. These two algorithms are applied to multichannel blind deconvolution task and their performance is compared. The rigorous derivation of algorithms and computer simulation results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.8
• /
• pp.1885-1896
• /
• 1996

This paper describes the implementation of the AVT(Automatic video Tracker) using ASIC. The basic tracking algorithm is based on the spatio-temporal gradient method, and adaptive window sizing, track state decision algorithm were also realized. Newly developed ASIC performs recursive image filtering, extraction of spatio-temporal gradient/gradient functions of image in field rate. Using the FPGA/ASIC, the tracker was simply realized in one board type which can be easily applied to various image system. We conformed ASIC operation by computer simulation and tested the system in real tracking situations. From the result, the system can track the moving target which has a velocity of 2-3 pixel/field and a size of varying from 2 to 128 pixes. Also fast refresh rateof motion estimation(60Hz) improves the characteristics of servoing system which forms feedback loop with the tracker.

• Journal of Broadcast Engineering
• /
• v.15 no.4
• /
• pp.474-486
• /
• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.22 no.3
• /
• pp.286-295
• /
• 2016

With the results of observations in 2013 and 2014 including ocean buoys, in-situ investigations and wind data, we examined the spatio-temporal variation of cold water masses along the eastern coast of Korea. Usually, a cold water mass first appears along the northern part of the eastern coast from May to July, and then along the southern part of the eastern coast from late June to mid-August. Cold water masses appear 3~5 times a year and remain for 5~20 days in the southwestern part of the East Sea. A distinctive cold water mass appeared usually in mid-July in this area, the surface temperature of which was below $10^{\circ}C$ in some cases. During the appearance of a cold water mass in the southwestern part of the East Sea, the horizontal temperature gradient was large at the surface and a significant low water temperature below $8^{\circ}C$ appeared at the bottom level. This appearance of cold water masses clearly corresponded to southwesterly winds, which generated coastal upwelling.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.1
• /
• pp.78-87
• /
• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.4 no.3
• /
• pp.126-133
• /
• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.2
• /
• pp.59-68
• /
• 1993

The motion vector estimation and motion boundary detection have been briskly studied since they are an important clue for analysis of object structure and 3-d motion. The purpose of this researches is more exact estimation, but there are two main causes to make inaccurate. The one is the erroneous measurement of gradients in brightness values and the other is the blurring of motion boundries which is caused by the smoothness constraint. In this paper, we analyze the gradient measurement error of conventional methods and propose new technique based on it. When the proposed method is applied to the motion boundary detection in Schunck and motion vector estimation in Horn & Schunck, it is shown to have much better performance than conventional method is some artificial and real image sequences.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.349-352
• /
• 2000

영상으로부터 의미있는 객체를 영역화하기 위하여, 움직임에 의한 시간적 정보를 이용하거나, 형태학적(Morphological) 기법과 같이 공간적 정보를 이용하는 방법이 있다. 그러나, 단지 시간적 정보나 공간적 정보만을 이용하는 방법은 그 한계를 가지고 있으며, 본 논문에서는 시공간 정보를 이용하여 분할하는 방법을 채택하였다. 시간적 분할에서는, 두 프레임에서 움직임 정보를 찾아내었던 기존 방법을 보완하여 연속되는 세 프레임을 사용하도록 하였다. 이렇게 하면 움직임이 미세한 영상에 대해서도 객체를 분리해 낼 가능성을 높일 수 있게 된다. 공간적 분할시에는, Watershed 알고리즘을 이용하는 형태학적 분할(Morphological Segmentation)[1][2]을 하게 되는데, 전처리 과정의 단일척도경사(Monoscale Gradient) 대신 다중척도 경사(Multiscale Gradient)[3][4]를 사용하여 미세한 경사는 누그러뜨리고 에지 부분의 경사만을 강조하게 하였다. 또한 개선된 Watershed 알고리즘을 제안하여 기존의 Watershed 알고리즘의 과분할 문제를 보완하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.8
• /
• pp.1319-1324
• /
• 2002

In this paper, we present a new technique for extraction of moving objects in moving image sequence. The detection method of change regions is based on spatial gradient difference and temporal difference. Moving objects are extracted by motion information and prediction error of each region. In the simulation results, the proposed technique shows good performance.