• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.317-326
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• 2002

The adaptive coding schemes in H.264 standardization provide a significant ceding efficiency and some additional features like error resilience and network friendliness. The variable block size motion compensation using multiple reference frames is one of the key H.264 coding elements to provide main performance gain, but also the main culprit that increases the overall computational complexity. For this reason, this paper proposes a selective motion estimation algorithm based on variable block size for fast motion estimation in H.264. After we find the SAD(Sum of Absolute Difference) at initial points using diamond search, we decide whether to perform additional motion search in each block. Simulation results show that the proposed method is five times faster than the conventional full search in case of search range $\pm$32.

• ETRI Journal
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• v.25 no.6
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• pp.489-502
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• 2003

This paper presents an MPEG-4 video codec, called MoVa, for video coding applications that adopts 3G-324M. We designed MoVa to be optimal by embedding a cost-effective ARM7TDMI core and partitioning it into hardwired blocks and firmware blocks to provide a reasonable tradeoff between computational requirements, power consumption, and programmability. Typical hardwired blocks are motion estimation and motion compensation, discrete cosine transform and quantization, and variable length coding and decoding, while intra refresh, rate control, error resilience, error concealment, etc. are implemented by software. MoVa has a pipeline structure and its operation is performed in four stages at encoding and in three stages at decoding. It meets the requirements of MPEG-4 SP@L2 and can perform either 30 frames/s (fps) of QCIF or SQCIF, or 7.5 fps (in codec mode) to 15 fps (in encode/decode mode) of CIF at a maximum clock rate of 27 MHz for 128 kbps or 144 kbps. MoVa can be applied to many video systems requiring a high bit rate and various video formats, such as videophone, videoconferencing, surveillance, news, and entertainment.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.679-684
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• 1989

In this paper, we describe the PTP notion of robot manipulators by neural networks. The PTP motion requires the inverse kinematic redline and the joint trajectory generation algorithm. We use the multi-layered Perceptron neural networks and the Error Back Propagation(EBP) learning rule for inverse kinematic problems. Varying the number of hidden layers and the neurons of each hidden layer, we investigate the performance of the neural networks. Increasing the number of learning sweeps, we also discuss the performance of the neural networks. We propose a method for solving the inverse kinematic problems by adding the error compensation neural networks(ECNN). And, we implement the neural networks proposed by Grossberg et al. for automatic trajectory generation and discuss the problems in detail. Applying the neural networks to the current trajectory generation problems, we can refute the computation time for trajectory generation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.618-622
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• 2009

An improvement of standard encoder has been saturated recently. However, new coding method does not have a compatibility with conventional standard. To solve this problem, new concept coding method that has a semicompatibility with standard may be discussed. On the other hand, cyclic Intra-picture coding is used for access and refreshment. However, I-picture spend large amount of bits. An enhancement of I-picture is desired with keeping its refreshment performance. Further, it's a problem that quality change at the border of GOP because of its independency. To respond these, we propose the coding which is applied an inter-frame processing at the border of GOP. Applied method is the reduction of quantization error using the motion compensated inter-picture processing. In this report, we check the improvement of the efficiency and the compatibility of proposed method. As a result of examination, we recognize that the total gain is maximally 1.2dB in PSNR. Generally, the degradation of performance in standard decoding is smaller than its gain. Also the refreshment performance is tested.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.571-578
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• 2002

In this paper, we propose a video sequence coding scheme called AMV (Auxiliary Motion Vector) to minimize error propagation caused by transmission errors over the Internet. Unlike the conventional coding schemes the AMY coder, for a macroblock in a frame, selects two best matching blocks among several preceding frames. The best matching block, called a primary block, is used for motion compensation of the destination macroblock. The other block, called an auxiliary block, replaces the primary block in case of its loss at the decoder. When a primary block is corrupted or lost during transmission, the decoder can efficiently and simply suppress error propagation to the subsequent frames by replacing the block with an auxiliary block. This scheme has an advantage of reducing both the number and the impact of error propagations. We implemented the proposed coder by modifying H.263 standard coding and evaluated the performance of our proposed scheme in the simulation. The simulation results show that AMV coder is more efficient than the H.263 baseline coder at the high packet loss rate.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.14-23
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• 1993

This paper proposes an algorithm to reduce the bitrate for transmission of MCP(motion compensated prediction) error signals. Many digital image coders have recently employed hybrid coding schemes which perform motion compensation, DCT transform, quantization, and variable length coding. The variable length coding compresses the quantized DCT coefficient data by removing their statistical redundancy. But some DCT blocks have the interblock statistical redundancy as well as the intrablock one. To utilize both of them, the DCT blocks are classified into the interleaving group and the non-interleaving group. And then each DCT blocks in the interleaving group are is encoded independently, and the DCT blocks in the interleaving group are encoded after interleaving the DCT coefficients. Through the simulations, it is shown that the proposed method outperforms the conventional method in which each DCT block is encoded independently.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.91-94
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• 2005

A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigate three sensor models: Collinearity model, Direct Linear Transform (DLT) model and Orbit-based model. We apply matching between GOES images and global coastline database and use successful results as control points. With control points we improve the initial image geolocation accuracy using the three models. We compare results from three sensor models that are applied to GOES-9 images. As a result, a suitable sensor model for precise geolocation of GOES-9 images is proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.530-536
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• 2004

In this paper a servo-system is developed to improve straightness of linear motor stages. When a linear motor stage is used for high-precision linear motion systems, high precision straightness accuracy is necessary to meet the required position accuracy. In such cases, machining and assembling cost increases to improve the straightness accuracy. An electro-magnetic actuator which is relatively cost effective than any other conventional servo-systems is suggested to compensate the fixed straightness error. To overcome the compensation error due to the friction, a sliding mode control is applied. The effectiveness of the suggested mechanism and the control performance are illustrated along with some experimental results.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.30-36
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• 2004

The development of LD(Laser Diode) tester and its control system based on the graphical programming language(LabVIEW) is addressed. The ill tester is used to check the optic power and the optic spectrum of the LD Chip. The emitter size of LD chip and the diameter of the Detector(optic fiber and photo diode) are very small, therefore the test device needs high accuracy. But each motion part of the test device could not accomplish high accuracy due to the limit of the mechanical performance. So, an image processing with machine vision is proposed to compensate for the error. By adopting our method we can reduce the error of position within $\pm$5$\mu\textrm{m}$.