• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.76-84
• /
• 2014

As the number of high-density videos increase, parallel processing approaches are necessary to process a large-scale of video data. When a processing method of video data requires thousands of simple operations, GPU-based parallel processing is preferred to CPU-based parallel processing by way of reducing the time and space complexities of a given computation problem. This paper studies the parallel design and implementation of a shot-boundary detection algorithm. The proposed shot-boundary detection algorithm uses pixel brightness comparisons and global histogram data among the blocks of frames, and the computation of these data is characterized with the high parallelism for the related operations. In order to maximize these operations in parallel, the computations of the pixel brightness and histogram are designed in parallel and implemented in NVIDIA GPU. The GPU-based shot detection method is tested with 10 videos from the set of videos in National Archive of Korea. In experiments, the detection rate is similar but the computation time is about 10 time faster to that of the CPU-based algorithm.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.30 no.3
• /
• pp.181-193
• /
• 2010

The paper presents an alternative way to classical stereocorrelation. First, 2D image processing of random patterns is described. Sub-pixel displacements are determined using phase analysis. Then distortion evaluation is presented. The distortion is identified without any assumption on the lens model because of the use of a grid technique approach. Last, shape measurement and shape variation is caught by fringe projection. Analysis is based on two pin-hole assumptions for the video-projector and the camera. Then, fringe projection is coupled to in-plane displacement to give rise to 3D measurement set-up. Metrological characterization shows a resolution comparable to classical (stereo) correlation technique ($1/100^{th}$ pixel). Spatial resolution seems to be an advantage of the method, because of the use of temporal phase stepping (shape measurement, 1 pixel) and windowed Fourier transform (in plane displacements measurement, 9 pixels). Two examples are given. First one is the study of skin properties; second one is a study on leather fabric. In both cases, results are convincing, and have been exploited to give mechanical interpretation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1235-1238
• /
• 2004

Thresholding has been used to reduce the number of gray values in images. Typically, a single threshold value has been used, resulting in two gray level images. Image reduction of one single threshold value, however, may lose too much of the high-frequency edge information. Thus, dynamic thresholding that uses a different threshold for each pixel is preferred instead of using a single threshold value. Dynamic thresholding can preserve high frequency details as well as reduce the size of images. Since it takes long time to perform existing software dynamic thresholding in an embedded system, this paper proposes and implements a circuit by using a FPGA in order to perform a real-time dynamic thresholding,. The proposed circuit consists of two counters, and threshold look-up table, and control unit. The values of two counters determine each pixel position, the threshold look-up table converts each pixel value into other value, and the control unit generates necessary control signals. On arriving from a camera to the proposed circuit, each pixel is compared with its threshold value and is converted into other gray value. An image processing system by using the proposed circuit will be implemented and some experiments will be performed.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.12
• /
• pp.2931-2946
• /
• 1997

In multimedia information retrieval applications, content-based image retrieval is essential for retrieving relevant multimedia documents. The purpose of our paper is to provide effective representation and efficient retrieval of images when a pixel-level original image is automatically or manually transformaed into its iconic image containing meaningful graphic descriptions, called icon objects. For this, we first propose new spatial match representationschemes to describe spatial relationships between icon objects accurately by expressing them as rectangles, rather than as points. In order to accelerate image searching, we also design an efficient retrieval method using a two-dimensional signature file organization. Finally, we show from our experiment that the proposed representation schemes achieve better retrieval effectiveness than the 9-DLT (Direction Lower Triangular) scheme.

• Journal of Information Processing Systems
• /
• v.14 no.3
• /
• pp.666-679
• /
• 2018

The discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its low frequency component contains the basic information of an image. Based on this, a fragile watermarking using the local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBP pattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the least significant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of the proposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of the maximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that the proposed algorithm not only has lower watermark payloads, but also achieves good performance in tamper identification and localization for various attacks.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.625-628
• /
• 2010

This paper proposes a novel feature extraction method for unsupervised multispectral image segmentation based in one dimensional combined neighborhood differences (1D CND). In contrast with the original CND, which is applied with traditional image, 1D CND is computed on a single pixel with various bands. The proposed algorithm utilizes the sign of differences between bands of the pixel. The difference values are thresholded to form a binary codeword. A binomial factor is assigned to these codeword to form another unique value. These values are then grouped to construct the 1D CND feature image where is used in the unsupervised image segmentation. Various experiments using two LANDSAT multispectral images have been performed to evaluate the segmentation and classification accuracy of the proposed method. The result shows that 1D CND feature outperforms the spectral feature, with average classification accuracy of 87.55% whereas that of spectral feature is 55.81%.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.27-29
• /
• 2006

In this paper, we propose a new method of automatic white balance which is one of the image signal processing techniques. Our method is conceptually based on gray world assumption. However, while previous methods generate linear results as multiplying pixel values by a gain, our method generates non-linear results using the feature of B-Spline curves. The two merits of deriving non-linear results are preventing AWB failure from transforming strong color of high level into wrong color and well preserving original contrast of an input image.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.12
• /
• pp.27-33
• /
• 2016

In this paper, we propose the bilateral filter based on median value that can reduce random noise and impulse noise with minimal loss of contour information. In general, EO / IR camera to generate a random or impulse noise due to a number of reasons. This noise reduces the performance of detecting and tracking by signal processing. To reduce noise, our proposed bilateral filter sorts the values of the target pixel and the peripheral pixels, and extracts a median filter coefficients of the Gaussian type. Then to extract the Gaussian filter coefficient involved with the distance between the center pixel and the surrounding pixels. As using those filter coefficients, our proposed method can remove the various noise effectively while minimizing the loss of the contour information. To validate our proposed method, we present experimental results for several IR images.

• Journal of Biosystems Engineering
• /
• v.17 no.1
• /
• pp.65-78
• /
• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.6
• /
• pp.963-971
• /
• 1990

This paper proposes a memory intensive VLSI architecture for the realization of real-time 3x3 neighborhood processor based on the distributed arithmetic. The proposed architecture is characterized by a bit serial and multi-kernel parallel processing which exploits the pixel kernel parallelism and concurrency. The chip implements 8 neighborhood processing elements in parallel with efficirnt input and output modules which operate concurrently. Besides the a4chitectural design of a neighborhood processor, the design methodology using module generator concept has been considered and MOGOT(MOdule Generator Oriented VLSI design Tool) has been constructed based on the workstation. Based on these design environments MOGOT, it has been shown that the main part of the suggested architecture can be designed efficiently using 2\ulcorner double metal CMOS technology. It includes design of input delay and data conversion module, look-up table for inner product operation, carry save accumulator, output data converter and delay module, and control module.