• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1018-1025
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• 2011

Scalable Video Coding (SVC) extension of H.264/AVC is a new video coding standard for media convergence by providing diverse videos of different spatial-temporal-quality layers with a single bitstream. Recently, real-time SVC codecs are being developed for the application areas of surveillance video and mobile video, etc. This paper presents the design and implementation of a H.264/SVC decoder based on an embedded DSP using Open SVC Decoder (OSD) which is a real-time software decoder designed for the PC environment. The implementation consists of porting C code of the OSD software from PC to DSP environment, profiling the complexity performance of OSD with further optimization, and integrating the optimized decoder into the TI Davinci EVM (Evaluation Module). 50 QCIF/CIF frames or 15 SD frames per second can be decoded with the implemented DSP-based SVC decoder.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.151-161
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• 2009

Audio Video Standard (AVS) is the audio and video compression standard that was developed for domestic video applications in China. AVS employs low complexity tools to minimize degradation of RD performance of the state-the-art video codec, H.264/AVC. The AVS video codec consists of $8{\times}8$ block prediction and the same size transform to improve compression efficiency for VGA and higher resolution sequences. Currently, the AVS has been adopted more and more for IPTV services and mobile applications in China. So, many consumer electronics companies and multimedia-related laboratories have been developing applications and chips for the AVS. In this paper, we implemented the AVS video decoder and optimize it on TI's Davinci EVM DSP board. For improving the decoding speed and clocks, we removed unnecessary memory operations and we also used high-speed VLD algorithm, linear assembly, intrinsic functions and so forth. Test results show that decoding speed of the optimized decoder is $5{\sim}7$ times faster than that of the reference software (RM 5.2J).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.78-85
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• 2011

In this paper we proposed an intelligent PTZ camera system which detects, classifies and tracks moving objects. If a moving object is detected, features are extracted for classification and then realtime tracking follows. We used GMM for detection followed by shadow removal. Legendre moment is used for classification. Without auto focusing, we can control the PTZ camera movement by using center points of the image and object's direction, distance and velocity. To implement the realtime system, we used TI DM6446 Davinci processor. Throughout the experiment, we obtained system's high performance in classification and tracking both at vehicle's normal and high speed motion.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2064-2068
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• 2010

In this paper, we introduced a sequential intelligent image analysis system(SIIAS). This system is implemented using PTZ camera with intelligent analysis algorithm and TI's Davinci DM6446. Enter, abandon, removal and cross functions are included in our system. These functions can be used individually or in combination for object monitoring and tracking. Sequential intelligent function processing is more efficient than the previous one by virtue of accurate observation, wide area monitoring and low cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.311-317
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• 2011

In this paper, we proposed realtime image enhancing method on the three noise types of input images, such as haze, low contrast and back light images. Some conventional de-hazing algorithms have good performance but need large memories and high computational burdens. We proposed the efficient algorithm which not only removes the haze but also reduces memory usage and computational complexity. We implemented the realtime system by using DM6446 DSP chip, and it showed the excellent result in these three problems; haze, low contrast and back light. We implemented the system with the processing speed at 15 frames/sec.