Min-Seok Choi

A novel two stage template matching method for rotation and illumination invariance

Abstract Template matching is the process of determining the presence and the location of a reference image or an object inside a scene image under analysis by a spatial cross-correlation process. Conventional cross-correlation type algorithms are computationally expensive. Furthermore, when the object in the image is rotated, the conventional algorithms cannot be used for practical purposes. In this paper, an algorithm for a rotation invariant template matching method based on the combination of the projection method and Zernike moments is proposed. The algorithm consists of two stages. In the first stage, the matching candidates are selected using a computationally low cost feature. Frequency domain calculation was adopted to reduce the computational cost for this stage. In the second stage, rotation invariant template matching is performed only on the matching candidates using Zernike moments.

Reduction of Blocking Artifacts for HDTV using Offset-and-Shift Technique

This paper addresses an effective postprocessing technique to remove blocking artifacts, which severely degrade visual quality in block-based image coding. The proposed algorithm classifies blocks into four types based on directional activity and removes the blocking artifacts while preserving edges and texture information by applying different types and strength of filter for each block type. Moreover, the proposed scheme includes a two-dimensional filtering method in order to remove staircase noises and corner outliers around diagonal and curved edges. Experimental results show that the proposed algorithm outperforms a number of deblocking methods in the literature in terms of PSNR and subjective visual quality. Furthermore, the execution time of the proposed algorithm takes less than that of the other methods, and thus it can be incorporated into real-time applications for moving pictures as well as still images.

The description and retrieval of a sequence of moving objects using a shape variation map

Abstract Motion information in a video clip plays an important role in characterizing the content of the clip. In this paper, we propose the shape variation descriptor to describe and retrieve video clips based on the shape variation caused by object movement along time. Similar to accumulator cells, a shape variation map was first constructed by cumulating binary shape images in the sequence of the video clip. A shape descriptor called ART, obtained from the map, then becomes a feature set for the shape variation of the clip. Experimental results over hundreds of video and animation clips show that our approach of retrieving video clips based on shape variation compares favorably against an alternative edge based method.

Cooperative Path planning for Redundant Dual-arm robot Using Low-dimensional Sample-based algorithm

Abstract This research presents a low-dimensional sample-based path planning method for cooperative work of redundant dual-arm robot which has two humanlike 7 degrees of freedom robot arms. The main task for this system is to move an object from initial position to goal position while the end-effector of two arms concurrently grasp the object. To accomplish this work, we use redundant variables and absolute frame which is attached to the object. This method reduces the dimension of the sampling configuration space for the considering task 14 to 8. To more effectively find a path for the cooperative work of the system, we use a very simple equation that linearly changes the orientation of absolute frame from the start configuration to the goal configuration along a path. This equation further reduces the dimension of sampling configuration space 8 to 5. From this approach, we can effectively get a path for the cooperative work of humanoid type dual-arm robot using probabilistic roadmaps algorithm. To verify the proposed method, simulation program is developed and simulation is carried out with some specific setting. Simulation results show that proposed method effectively plans a cooperative path for the redundant dual-arm robot system.

Efficient Representation and Matching of Object Movement using Shape Sequence Descriptor

ABSTRACT Motion of object in a video clip often plays an important role in characterizing the content of the clip. A number of methods have been developed to analyze and retrieve video contents using motion information. However, most of these methods focused more on the analysis of direction or trajectory of motion but less on the analysis of the movement of an object itself. In this paper, we propose the shape sequence descriptor to describe and compare the movement based on the shape deformation caused by object motion along the time. A movement information is first represented a sequence of 2D shape of object extracted from input image sequence, and then 2D shape information is converted 1D shape feature using the shape descriptor. The shape sequence descriptor is obtained from the shape descriptor sequence by frequency transform along the time. Our experiment results show that the proposed method can be very simple and effective to describe the object movement and can be applicable to semantic applications such as content-based video retrieval and human movement recognition.Keywords:Shape sequence descriptor, Shape sequence, Movement recognition, Movement retrieval

Adaptive deblocking algorithm based on image characteristics for low bit-rate video

Reconstructed images in low bit-rate video coding often have visually annoying artifacts, such as blocking artifacts and corner outliers, usually due to block-based quantization and motion-compensated prediction. In this paper, we propose an adaptive deblocking algorithm based on local image characteristics. We remove ringing artifacts using a simple low-pass filter in the preprocessing. Among four filtering modes, an appropriate filter is selected adaptively, removing noticeable blocking artifacts in flat areas, while preserving details without blurring in highly complex areas. The proposed filter contains a non-symmetric filter a corner outlier removal filter. Simulation results show the effectiveness of the proposed deblocking algorithm in objective and subjective quality compared with those of the MPEG-4 deblocking filter.

An Efficient Motion Estimation Technique using the Spatial and Temporal Correlations

Motion Estimation (ME) is a core part of most Video compression systems since it affects directly the output video quality and the encoding time. The most basic method of ME, Full Search (FS) gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has been proposed. Among them, MVFAST and PMVFAST show impressive results in video quality and the computational load by using the correlation between motion vectors of adjacent blocks. In particular, PMVFAST reduces search points dramatically and also gives very high video quality by using the median predictor. In this paper, we propose a new algorithm that uses the redefined median predictor which reduces the number of search points and yields a high visual quality by reducing the number of thresholds and early termination conditions.

A method of describing and retrieving a sequence of moving object using Shape Variation Map

Motion Information in a video clip often plays an important role in characterizing the content of the clip. A number of methods have been developed to analyze and retrieve video contents using motion information. However, most of these methods focused more on the analysis of direction or trajectory of motion but less on the analysis of the movement of an object. In this paper, we introduce the shape variation descriptor for describing shape variation caused by object movement along time, and propose a method to describe and retrieve the shape variation of the object using shape variation map. The experimental results shows that the proposed method performed much better than the previous method by l1％ and is very effective for describing the shape variation which is applicable to semantic retrieval applications.