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A new rate control algorithm for videos is presented. The method comes from the MPEG-2 Test Model 5(TM5) rate control, while a buffer constraint and a new measure for the macroblock (MB) activity based on spatio-temporal sensitivity are introduced. Experimental results show that the proposed method outperforms the TM5 rate control in picture quality.

This paper presents a semi-automatic segmentation method based on user assistance and object tracking. In the method, a user can initially mark objects of interest around the object boundaries. Then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. Experimental results are presented to demonstrate the superiority of the proposed method over automatic methods.

A new vertex selection scheme using the curvature information of contour points for polygonal contour approximation is presented. The proposed method consists of two-step procedure. At first, we compute curvature values for contour points on the curvature scale space (CSS) and select high curvature points as principal vertices. Selected principal vertices, thereby, divide an overall contour into several contour segments. In the second step, the vertices for each contour segment are selected using the progressive vertex selection (PVS) method in order to obtain minimum number of vertices under the given maximum distance criterion (D*max).

This paper presents a modified MSEA (multi-level successive elimination algorithm) which gives less computational complexity. We predict a motion estimation error using the norms at the already processed levels in the MSEA scheme and then decide on if the following levels should be proceeded using the predicted result. We skip the computation at the following levels where the processing is no longer meaningful. At this point, skipping the processing gives computational gain compared to the conventional MSEA scheme. For the purpose of predicting the norm at each level, we first show the theoretical analysis of the norm at each level and then verify the analysis by experiments. Based on the analysis, a new motion estimation method is proposed and its performance is evaluated.

This paper presents a new watermarking scheme using the pattern-based image normalization. The proposed method extracts an image-adaptive binary pattern (BP) composed of inner regions, and the geometric moments are computed using the BP rather than the source image itself. This approach avoids any misalignment between the normalized images on both sides of embedding and detection, which is inevitable when the source image itself is used.

This paper presents a fast full search algorithm for motion estimation. The proposed method is an extended version of the rate constrained successive elimination algorithm (RSEA) for multiple reference frame applications. We will show that motion estimation for the reference images temporally preceding the first reference image can be less intensive in computation compared with that for the first reference image. For computational reduction, we will drive a new condition to lead the smaller number of candidate blocks for the best matched block. Simulation results explain that our method reduces computation complexity although it has the same quality as RSEA.