• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.413-414
• /
• 2006

In this paper, we propose an efficient coding method of digital hologram (or fringe pattern) using multi-view prediction technique based on video and image coding standard such as MPEG. The proposed algorithm illustrates that it has better properties for reconstruction and higher compression rate than the previous researches.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.512-517
• /
• 2011

In this paper, we propose an Active Shape Model (ASM) and Lucas-Kanade (LK) optical flow-based feature extraction and analysis method for analyzing the emotional features from facial images. Considering the facial emotion feature regions are described by Facial Action Coding System, we construct the feature-related shape models based on the combination of landmarks and extract the LK optical flow vectors at each landmarks based on the centre pixels of motion vector window. The facial emotion features are modelled by the combination of the optical flow vectors and the emotional states of facial image can be estimated by the probabilistic estimation technique, such as Bayesian classifier. Also, we extract the optimal emotional features that are considered the high correlation between feature points and emotional states by using common spatial pattern (CSP) analysis in order to improvise the operational efficiency and accuracy of emotional feature extraction process.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.77-83
• /
• 2015

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

• Journal of Broadcast Engineering
• /
• v.15 no.5
• /
• pp.653-664
• /
• 2010

Generally existing video codec employs entropy coding to deal with residual signals with considering temporal and spatial properties. Scalable Video Coding(SVC) which is extension of H.264/AVC has three technical concepts for removing redundancies between inter-layers. In spite of using novel prediction method between inter-layers in SVC, it is still using same entropy coding method to residual signals. According to the studies, the residual obtained by inter-layer prediction technique has different features of residual signal acquired by spatial or temporal prediction technique. In this paper, we propose an efficient entropy coding method which codes the residual signal obtained by inter-layer prediction with regarding its features adequately. We re-designed the Coded Block Pattern(CBP) table suitably for inter-layer texture prediction. The experiments show that the proposed method can further reduce the BD-Bitrate up to average 2.20% in 4CIF and 1.14% in CIF resolution compared to the existing JSVM 9.18.

• ETRI Journal
• /
• v.31 no.5
• /
• pp.607-609
• /
• 2009

In this letter, an effective scanning method based on a morphological representation of quantized coefficients is proposed for intra coding in H.264. In the proposed scanning method, the scan order for each block is adaptively reconfigured by exploiting a residual correlation beyond the border of the block. An initial scan order for the current block is determined first by using the pattern of nonzero coefficients in the adjacent block. Then, a complete scan order is obtained by performing the dilation operation at each position within the initial scan order. Experimental results show that the proposed method improves the coding efficiency up to 3.7% compared to the conventional zigzag scanning method.

• Journal of Korea Multimedia Society
• /
• v.9 no.11
• /
• pp.1445-1454
• /
• 2006

To compress a specific part of an image with high quality or to transfer it, JPEG2000 standard offers an ROI(Region-of-Interest) image coding method. What is important in ROI coding is to process relative importance between ROI and background and to process ROI mask. We propose an adaptive ROI coding method supplemented the existing Implicit ROI coding and Modified implicit ROI coding to improve image quality and reduce ROI mask information. The proposed method is an EBCOT-based ROI coding that extracts ROI from the compressed bitstream, and gets the ROI mask information by classifying the codeblocks into 6 patterns. The information includes the pattern type(3bit) and the width(5bit) expressing the boundary between two regions for each codeblock. As a result, the method shows an excellent compression performance in ROI region as well as in the whole region of an image.

• Journal of Broadcast Engineering
• /
• v.8 no.2
• /
• pp.181-197
• /
• 2003

Notion Compensation(MC) technique using Sub-Band Coding with the hierarchical structure is efficient to estimate real motion. In the hierarchical pyramid method, low-band MC pyramid method is popular, where the upper layer estimate the glover motion and next lower layer estimate the local motion. The low-band MC pyramid scheme has two problems. First, because the quantization errors at lower layer are accumulated when using coding and quantizing, it is impossible to search the exact Motion Vector(MV) Second, because of the top-down search problem in the hierarchical structure, MV mismatch in upper layer causes serious MV in lower layer So. we propose new hierarchical MC pyramid method based on edge classification. In this Paper, we show that the performance of proposed Pass-band motion compensation pyramid technique is better than low-band motion compensation pyramid. Also, in the pyramid motion estimation, we propose initial MV estimation scheme based on the edge-pattern classification. As a result, we find that PSNR was increased.

• Proceedings of the IEEK Conference
• /
• 2000.06d
• /
• pp.39-42
• /
• 2000

Motion estimation plays an important role for video coding. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of block shape and size, we can find an optimal search pattern for initial motion estimation. The proposed idea, which has been verified experimentally by computer simulations, can provide an analytical basis for the current MPEG-2 proposals. In order to choose a more compact search pattern for BMA, we exploit the statistical relationship between the motion and the frame difference of each block.

• Journal of Auto-vehicle Safety Association
• /
• v.8 no.1
• /
• pp.19-25
• /
• 2016

As new car technology is developing, temporal interaction is needed in automotive. Rhythmic pattern is one of the practical examples of temporal interaction in vehicle. To recognize rhythmic pattern and its input medium, dictionary learning is applicable algorithm. In this paper, performance and memory requirement of the learning algorithm is tested and is sufficiently good for use this acoustic sound.

• Journal of KIISE:Software and Applications
• /
• v.32 no.12
• /
• pp.1260-1270
• /
• 2005

Support Vector Machines (SVM) is well known for a representative learner as one of the kernel methods. SVM which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, SVM is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with a binary SVM. One-Per-Class (OPC) and All-Pairs have been applied to solve the face recognition problem, which is one of the multi-class problems, with SVM. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. In this paper, we introduce the output coding methods as an approach for extending binary SVM to multi-class SVM and propose new output coding schemes based on the Error-Correcting Output Codes (ECOC) which is a dominant theoretical foundation of the output coding methods. From the experiment on the face recognition, we give empirical results on the properties of output coding methods including our proposed ones.