• Journal of Information Processing Systems
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• v.18 no.2
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• pp.235-244
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• 2022

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1563-1571
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• 2009

In this paper, we propose a new boundary matching method for the temporal error concealment and a post processing algorithm for perceptual quality improvement of the concealed frame. Temporal error concealment is a method that substitutes error blocks with similar blocks from the reference frame. In conventional H.264/AVC standard, it compares outside pixels of erroneous block with inside pixels of reference block to find the most similar block. However, it is very possible that the conventional method substitutes erroneous block with the wrong one because it compares only narrow spatial range of pixels. In this paper, for substituting erroneous blocks with more correct blocks, we propose enhanced boundary matching method by comparing inside and outside pixels of reference block with outside pixels of erroneous block and setting up additional candidate motion vector in the fixed search range based on maximum and minimum value of candidate motion vectors. Furthermore, we propose a post processing method to smooth edges between concealed and decoded blocks without error by using the modified deblocking filter. We identified that the proposed method shows quality improvement of about 0.9dB over the conventional boundary matching methods.

• Journal of Advanced Navigation Technology
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• v.22 no.1
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• pp.20-26
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• 2018

In this paper, we propose a moving object detection and tracking algorithm based on multi-frame feature point tracking information to reduce false positives. However, there are problems of detection error and tracking speed in existing studies. In order to compensate for this, we first calculate the corner feature points and the optical flow of multiple frames for camera movement compensation and object tracking. Next, the tracking error of the optical flow is reduced by the multi-frame forward-backward tracking, and the traced feature points are divided into the background and the moving object candidate based on homography and RANSAC algorithm for camera movement compensation. Among the transformed corner feature points, the outlier points removed by the RANSAC are clustered and the outlier cluster of a certain size is classified as the moving object candidate. Objects classified as moving object candidates are tracked according to label tracking based data association analysis. In this paper, we prove that the proposed algorithm improves both precision and recall compared with existing algorithms by using quadrotor image - based detection and tracking performance experiments.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.169-179
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• 2013

Change detection algorithms take two image frames and return the locations of newly introduced objects which cause differences between the images. This paper presents a new change detection method, which classifies intensity changes due to introduced objects, reflected light and shadow from the objects to their neighborhood, and the noise, and exactly localizes the introduced objects. For classification and localization, first we analyze the histogram of the intensity difference between two images, and estimate multiple threshold values. Second we estimate candidate object boundaries using the gradient difference between two images. Using those threshold values and candidate object boundaries, we segment the frame difference image into multiple regions. Finally we classify whether each region belongs to the introduced objects or not using textures in the region. Experiments show that the proposed method exactly localizes the objects in various scenes with different lighting.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1229-1233
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• 2006

To find the candidate genes concerned with ovulation rate of sheep, Differential Display Reverse Transcription Polymerase Chain Reaction was employed to find the differently expressed cDNA controlling ovulation in the Small Tail Han sheep of polyembryony and in Tan sheep of single birth. Twenty-four primer pairs of three anchored primers and eight arbitrary primers were assembled to amplify the specialized bands from these sheep. Positive cross tests were applied to optimize the ascertainable PCR conditions in which different special bands can be identified by silver strain in one PCR tube. After eliminating the false positive PCR products by Northern hybridization, 24 differential display bands were acquired from the ovary in the Small Tail Han sheep. These EST bands were sequenced and 18 different ESTs were found in which five ESTs had several copies and 13 ESTs had only one copy. Comparing these ESTs with homologous sequences by BLAST in the GenBank, there were six ESTs with known open reading frame (ORF) and function, three ESTs with known ORF and no function, and 9 ESTs without homologous sequence. These ESTs partly represent several genes such as NOS2, tensin, TCRA, CDKN1A, ESR1 and ACTB which express especially in Small Tail Han sheep.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2430-2436
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• 2013

This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.367-376
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• 2009

In this paper, we propose a flame detection method using Haar wavelet and moving averages in outdoor infrared video sequences. Our proposed method is composed of three steps which are Haar wavelet decomposition, flame candidates detection, and their tracking and flame classification. In Haar wavelet decomposition, each frame is decomposed into 4 sub- images(LL, LH, HL, HH), and also computed high frequency energy components using LH, HL, and HH. In flame candidates detection, we compute a binary image by thresholding in LL sub-image and apply morphology operations to the binary image to remove noises. After finding initial boundaries, final candidate regions are extracted using expanding initial boundary regions to their neighborhoods. In tracking and flame classification, features of region size and high frequency energy are calculated from candidate regions and tracked using queues, and we classify whether the tracked regions are flames by temporal changes of moving averages.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.243-248
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• 2013

In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.

• Journal of The Korean Astronomical Society
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• v.52 no.3
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• pp.57-69
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• 2019

We present an analysis of the chemical abundances and kinematics of six low-mass dwarf stars, previously claimed to be candidate hypervelocity stars (HVSs). We obtained moderate-resolution (R ~ 6000) spectra of these stars to estimate the abundances of several chemical elements (Mg, Si, Ca, Ti, Cr, Fe, and Ni), and derived their space velocities and orbital parameters using proper motions from the Gaia Data Release 2. All six stars are shown to be bound to the Milky Way, and in fact are not even considered high-velocity stars with respect to the Galactic rest frame. Nevertheless, we attempt to characterize their parent Galactic stellar components by simultaneously comparing their element abundance patterns and orbital parameters with those expected from various Galactic stellar components. We find that two of our program stars are typical disk stars. For four stars, even though their kinematic probabilistic membership assignment suggests membership in the Galactic disk, based on their distinct orbital properties and chemical characteristics, we cannot rule out exotic origins as follows. Two stars may be runaway stars from the Galactic disk. One star has possibly been accreted from a disrupted dwarf galaxy or dynamically heated from a birthplace in the Galactic bulge. The last object may be either a runaway disk star or has been dynamically heated. Spectroscopic follow-up observations with higher resolution for these curious objects will provide a better understanding of their origin.