• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.85-88
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• 2017

보행자 검출을 위한 기술이 많이 개발되고 있으며 HOG(Histograms of oriented)와 haar-like feature를 이용한 특징값 검출을 통해 보행자를 검출하는 방법들이 대표적이라 할 수 있다. 하지만 이 방법들은 보행자가 사물에 가려졌을 때 보행자를 검출하지 못한다는 단점이 있다. 이에 본 논문에서는 haar-like feature와 adaboost 학습알고리듬을 이용하여 보행자를 검출하고 kalman filter를 이용하여 보행자가 특정 사물에 가려지는 것 과 같은 occlusion 문제를 해결하여 보행자 검출 성능을 높이고자 하였다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1988-1995
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• 2000

In this paper, we have proposed the contrast control method for improving image quality. The proposed method can be easily applied to the FPD (flat panel display) which requires real-time processing because of its lower hardware complexity that the conventional methods. In addition, it can flexibly control the contrast of input image by arraying the weight values that control the contrast range. Visual test and standard deviation of their histograms have been introduced to evaluate the results of proposed method and the original images. The functional operation of he proposed method has been verified using the SYNOPSYS VHDL tool and computer simulation. Its results show that he proposed method might be very suitable for real-time processing on the FPD.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1607-1612
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• 2007

It necessarily follows that wear particles are generated through a friction and wear in a mechanical moving system. The wear particles are relative to the failure and the life of machine elements directly. To analyze the wear particle, its shape characteristics were calculated quantitative values such as diameter, roundness and fractal parameters by digital image processing. In this study, the histograms of shape parameters of wear particles were used for the purpose of analyzing the distribution of wear particles in various conditions. We consider that the histogram of shape parameter can be effectively represented to study a wear mechanism.

• Smart Structures and Systems
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• v.6 no.1
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• pp.17-27
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• 2010

The approach to damage detection and localization adopted in this paper is based on a statistical comparison of models built from the response time histories collected at different stages during the structure lifetime. Some of these time histories are known to have been recorded when the structural system was undamaged. The consistency of the models associated to two different stages, both undamaged, is first recognized. By contrast, the method detects the discrepancies between the models from measurements collected for a damaged situation and for the undamaged reference situation. The damage detection and localization is pursued by a comparison of the SSE (sum of the squared errors) histograms. The validity of the proposed approach is tested by applying it to the analytical benchmark problem developed by the ASCE Task Group on Structural Health Monitoring (SHM). In the paper, the results of the benchmark studies are presented and the performance of the method is discussed.

• Structural Engineering and Mechanics
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• v.26 no.2
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• pp.191-210
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• 2007

The three different approaches (reformulations) of evolution strategies (ESs) have been proposed in the literature as extensions of the technique for solving discrete problems. This study implements an extensive research on application, evaluation and comparison of them in discrete optimum design of steel frames. A unified formulation is first developed to explain these approaches, so that differences and similarities between their inherent search mechanisms can clearly be identified. Two examples from practical design of steel frames are studied next to measure their performances in locating the optimum. Extensive numerical experimentations are performed in both examples to facilitate a statistical analysis of their convergence characteristics. The results obtained are presented in the histograms demonstrating the distribution of the best designs located by each approach. In addition, an average improvement of the best design during the course of evolution is plotted in each case to compare their relative convergence rates.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4869-4873
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• 2016

Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods.

• International Journal of Contents
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• v.12 no.1
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• pp.1-5
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• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.224-229
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• 2011

Cellular Automata is a discrete dynamical system that can be completely described in terms of local relation. For any given image, the system can save its features as well as increase or decrease the brightness of it locally through consideration of optimized transition in succession. These transitions in succession satisfy the function "Lyapunov" and have sequential movements. This study suggests the way of noise reduction for each image with the use of the Sequential Cellular Automata system. The mentioned transition in succession gives stable results with high-convergence performance to random noises and PSNR (Peak Signal-to-Noise Ratio) using histograms and MSE (Mean Square Error) for verification of effectiveness.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.