• Journal of Broadcast Engineering
• /
• v.14 no.2
• /
• pp.127-133
• /
• 2009

With advances in video technology, many researchers are interested in video quality assessment to prove better performance of proposed algorithms. Since human visual system is too complex to be formulated exactly, many researches about video quality assessment are in progressing. No-reference video-quality assessment is suitable for various video streaming services, because of no requested additional data and network capacity to perform quality assessment. In this paper, we propose a novel no-reference video-quality assessment method with the estimation of dynamic range distortion. To measure the performance, we obtain mean opinion score (MOS) data by subject video quality test with the ITU-T P.910 Absolute Category Rating (ACR) method. And, we compare it with proposed algorithm using 363 video sequences. Experimental results show that the proposed algorithm has a higher correlation with obtained MOS.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8C
• /
• pp.790-800
• /
• 2009

For the improvement of coding efficiency, the H.264/AYC standard uses new coding tools such as 1/4-pel-accurate motion estimation, multiple references, intra prediction, loop filter, variable block size etc. Using these coding tools, H.264/AYC has achieved significant improvements from rate-distortion point of view compared to existing standards. However, the encoder complexity was greatly increased due to these coding tools. We focus on the complexity reduction method of intra macroblock mode selection. The proposed algorithm for fast intra mode selection calculates the edge activity in transform domain, and performs fast encoding of intra frame in H.264/AYC through the fast prediction mode selection of intra4x4 and chrominance blocks. Simulation results show that the proposed method saves about 59.76% for QCIF sequences and 65.03% for CIF sequences of total encoding time, while bitrate increase and PSNR decrease are very small.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.2
• /
• pp.69-78
• /
• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.