• 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.

• International Journal of Contents
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• v.8 no.1
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• pp.16-22
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• 2012

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.

• 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.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.32-35
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• 2013

In this paper we proposed a PTZ camera system which automatically detect and track moving objects in the image. Once a moving object is detected the PTZ camera traces it in real-time. We proposed the control system which does not depend on camera focusing functionality but uses the object's center, moving direction, distance and speed. We implemented the system with the TI DM6446 DSP chip. The experimental result shows that the system has excellent performance for high speed vehicles.

• 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).