• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.108-115
• /
• 2009

In this paper, we propose a novel true-motion estimation technique supporting efficient frame error concealment for error-resilient video coding. In general, it is important to accurately obtain the true-motion of objects in video sequences for effectively recovering the corrupted frame due to transmission errors. However, the conventional motion estimation (ME) technique, which minimizes a sum of absolute different (SAD) between pixels of the current block and the motion-compensated block, does not always reflect the true-movement of objects. To solve this problem, we introduce a new metric called an absolute difference of motion vectors (ADMV) which is the distance between motion vectors of the current block and its motion-compensated block. The proposed ME method can prevent unreliable motion vectors by minimizing the weighted combination of SAD and ADMV. In addition, the proposed ME method can significantly improve the performance of error concealment at the decoder since error concealment using the ADMV can effectively recover the missing motion vector without any information of the lost frame. Experimental results show that the proposed method provides similar coding efficiency to the conventional ME method and outperforms the existing error-resilient method.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.97-107
• /
• 2009

In image-based gait recognition systems, physical factors, such as the camera angle and the lens distortion, and environmental factors such as illumination determines the performance of recognition. In this paper we present a robust gait recognition method by compensating various types of image distortions. The proposed method is compared with existing gait recognition algorithm with consideration of both physical and environmental distortion factors in the input image. More specifically, we first present an efficient compensation algorithm of image distortion by using the projective transform, and test the feasibility of the proposed algorithm by comparing the recognition performances with and without the compensation process. Proposed method gives universal gait data which is invariant to both distance and environment. Gained data improved gait recognition rate about 41.5% in indoor image and about 55.5% in outdoor image. Proposed method can be used effectively in database(DB) construction, searching and tracking of specific objects.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.65-77
• /
• 2009

This paper proposes fast image processing algorithms using SSE (Streaming SIMD Extensions) instructions. The CPU's supporting SSE instructions have 128bit XMM registers; data included in these registers are processed at the same time with the SIMD (Single Instruction Multiple Data) mode. This paper develops new SIMD image processing algorithms for Mean filter, Sobel horizontal edge detector, and Morphological erosion operation which are most widely used in automated optical inspection systems and compares their processing times. In order to objectively evaluate the processing time, the developed algorithms are compared with OpenCV 1.0 operated in SISD (Single Instruction Single Data) mode, Intel's IPP 5.2 and MIL 8.0 which are fast image processing libraries supporting SIMD mode. The experimental result shows that the proposed algorithms on average are 8 times faster than the SISD mode image processing library and 1.4 times faster than the SIMD fast image processing libraries. The proposed algorithms demonstrate their applicability to practical image processing systems at high speed without commercial image processing libraries or additional hardwares.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.58-66
• /
• 2009

Recently the emerging demands of the light-video encoder promotes lots of research efforts on DVC (Distributed Video Coding). As an appropriate video compression method, DVC has been studied, and Wyner-Ziv (WZ) video compression is its one representative structure. The WZ encoder splits the image into two kinds of frames, one is key frame which is compressed by conventional intra coding, and the other is WZ frame which is encoded by WZ coding. The WZ decoder decodes the key frame first, and estimates the WZ frame using temporal correlation between key frames. Estimated WZ frame (Side Information) cannot be the same as the original WZ frame due to the absence of the WZ frame information at decoder. As a result, the difference between the estimated and original WZ frames are regarded as virtual channel noise. The WZ frame is reconstructed by removing noise in side information. Therefore precise noise estimation produces good performance gain in WZ video compression by improving error correcting capability by channel code. But noise cannot be estimated precisely at WZ decoder unless there is good WZ frame information, and generally it is estimated from the difference of corresponding key frames. Also the estimated noise is limited by comparing with frame level noise to reduce the uncertainty of the estimation method. However these methods cannot provide good noise estimation for every frame or each bit plane. In this paper, we propose a noise nodel selection method which chooses a better noise model for each bit plane after generating candidate noise models. Experimental result shows PSNR gain up to 0.8 dB.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.89-98
• /
• 2009

In the field of computer vision, image mosaicking is a common method for effectively increasing restricted the field of view of a camera by combining a set of separate images into a single seamless image. Image mosaicking based on feature points has recently been a focus of research because of simple estimation for geometric transformation regardless distortions and differences of intensity generating by motion of a camera in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.42-49
• /
• 2009

This paper proposes a driving current control method for a back light unit (BLU), consisting of red, green, and blue (RGB) light-emitting diodes (LEDs), whereby an RGB optical sensor is used to check the output color stimulus variation to enable a time-stable color stimulus for light emission by the RGB LED BLU. First, to obtain the present color stimulus information of the RGB LED BLU, an RGB to XYZ transform matrix is derived to enable CIEXYZ values to be calculated for the RGB LED BLU from the output values of an RGB optical sensor. The elements of the RGB to XYZ transform matrix are polynomial coefficients resulting from a polynomial regression. Next, to obtain the proper duty control values for the current supplied to the RGB LEDs, an XYZ to Duty transform matrix is derived to calculate the duty control values for the RGB LEDs from the target CIEXYZ values. The data used to derive the XYZ to Duty transform matrix are the CIEXYZ values for the RGB LED BLU estimated from the output values of the RGB optical sensor and corresponding duty control values applied to the RGB LEDs for the present, first preceding, and second preceding sequential check points. With every fixed-interval check of the color stimulus of the RGB LED BLU, the XYZ to Duty transform matrix changes adaptively according to the present lighting condition of the RGB LED BLU, thereby allowing the RGB LED BLU to emit the target color stimulus in a time-stable format regardless of changes in the lighting condition of the RGB LEDs.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.5
• /
• pp.45-53
• /
• 2007

To recover transmitted signal perfectly at DTV receiver, we have to acquire carrier frequency synchronization to compensate pilot signal which located in wrong position and rotated phase. Also, we need a symbol timing synchronization to compensate sampling timing error. Conventionally, to synchronize symbol timing, we use Gardner's scheme which used in multi-level signal. Gardner's scheme is well known for its sampling the timing error signal from every symbol and it makes easy to detect and keep timing sync in multi-path channel. In this paper, to discuss the problem when the received power level is out of range and we cannot get synchronization information. With this problem, we use 2 step procedures. First, we put a received signal power compensation block before Garder's timing error detector. Second, adaptive loop filter to get a fast synchronization information and averaging loop filter's output value to reduce the amount of jitter after synchronization in PLL(Phased Locked Loop) circuit which is used to get a carrier frequency synchronization and symbol timing synchronization. Using the averaging value, we can estimate offset. Based on offset changing ratio, we can adapt adaptive loop filter to carrier frequency and symbol timing synchronization circuit.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.5
• /
• pp.103-111
• /
• 2007

In this paper, we propose a VLSI architecture of hardware optimized high quality image signal processor for a Single-chip CMOS Image Sensor(CIS). The Single-chip CIS is usually used for mobile applications, so it has to be implemented as small as possible while maintaining the image quality. Several image processing algorithms are used in ISP to improve captured image quality. Among the several image processing blocks, demosaicing and image filter are the core blocks in ISP. These blocks need line memories, but the number of line memories is limited in a low cost Single-chip CIS. In our design, high quality edge-adaptive and cross channel correlation considered demosaicing algorithm is adopted. To minimize the number of required line memories for image filter, we share the line memories using the characteristics of demosaicing algorithm which consider the cross correlation. Based on the proposed method, we can achieve both high quality and low hardware complexity with a small number of line memories. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 37K, and seven and half line memories are used.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.5
• /
• pp.1-10
• /
• 2007

Most of natural images have a special property, what is called self-similarity, which is the basis of fractal image coding. Even though an image has local stationarity in several homogeneous regions, it is generally non-stationarysignal, especially in edge region. This is the main reason that poor results are induced in linear techniques. In order to overcome the difficulty we propose a non-linear technique using self-similarity in the image. In our work, an image is classified into stationary and non-stationary region with respect to sample variance. In case of stationary region, do-noising is performed as simply averaging of its neighborhoods. However, if the region is non-stationary region, stationalization is conducted as make a set of center pixels by similarity matching with respect to bMSE(block Mean Square Error). And then do-nosing is performed by Gaussian weighted averaging of center pixels of similar blocks, because the set of center pixels of similar blocks can be regarded as nearly stationary. The true image value is estimated by weighted average of the elements of the set. The experimental results show that our method has better performance and smaller variance than other methods as estimator.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.6
• /
• pp.100-110
• /
• 2007

When compressed video data is transmitted over error-prone network such as wireless channel, data is likely to be lost, so the quality of reconstructed picture is severely decreased. It is specially so in case that important information such as motion vector or macroblock mode is lost. H.264/AVC standard includes DP as error resilient technique for protecting important information from error in which data is labeled according to its relative importance. But DP technique requires a network that supports different reliabilities of transmitted data. In general, the benefits of UEP is sought by sending multiple times of same packets corresponding to important information. In this paper, we propose MDC technique based on data partitioning technique. The proposed method encodes motion vector of H.264/AVC standard into multiple parts using MDC and transmits each part as independent packet. Even if partial packet is lost, the proposed scheme can decode the compressed bitstream by using estimated motion vector with partial packets correctly transmitted, so that achieving improved performance of error concealment with minimal effect of channel error. Also in decoding process, the proposed multiple description matching increases the accuracy of estimated lost motion vector and quality of reconstructed video.