• Title/Summary/Keyword: Binary image

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Real-time Moving Object Tracking from a Moving Camera (이동 카메라 영상에서 이동물체의 실시간 추적)

  • Chun, Quan;Lee, Ju-Shin
    • The KIPS Transactions:PartB
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    • v.9B no.4
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    • pp.465-470
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    • 2002
  • This paper presents a new model based method for tracking moving object from a moving camera. In the proposed method, binary model is derived from detected object regions and Hausdorff distance between the model and edge image is used as its similarity measure to overcome the target's shape changes. Also, a novel search algorithm and some optimization methods are proposed to enable realtime processing. The experimental results on our test sequences demonstrate the high efficiency and accuracy of our approach.

Object Tracking with Sparse Representation based on HOG and LBP Features

  • Boragule, Abhijeet;Yeo, JungYeon;Lee, GueeSang
    • International Journal of Contents
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    • v.11 no.3
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    • pp.47-53
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    • 2015
  • Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

Algorithm of Morphological Multimode Binary Shape Decomposition (형태론적 다중모드 2진 형상분해 알고리즘)

  • Choi, Jong-Ho
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.9
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    • pp.67-75
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    • 1999
  • In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements tat are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have chatacteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

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Area Classification, Identification and Tracking for Multiple Moving Objects with the Similar Colors (유사한 색상을 지닌 다수의 이동 물체 영역 분류 및 식별과 추적)

  • Lee, Jung Sik;Joo, Yung Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.3
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    • pp.477-486
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    • 2016
  • This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

Lossless Coding Scheme for Lattice Vector Quantizer Using Signal Set Partitioning Method (Signal Set Partitioning을 이용한 격자 양자화의 비 손실 부호화 기법)

  • Kim, Won-Ha
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.93-105
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    • 2001
  • In the lossless step of Lattice Vector Quantization(LVQ), the lattice codewords produced at quantization step are enumerated into radius sequence and index sequence. The radius sequence is run-length coded and then entropy coded, and the index sequence is represented by fixed length binary bits. As bit rate increases, the index bit linearly increases and deteriorates the coding performances. To reduce the index bits across the wide range of bit rates, we developed a novel lattice enumeration algorithm adopting the set partitioning method. The proposed enumeration method shifts down large index values to smaller ones and so reduces the index bits. When the proposed lossless coding scheme is applied to a wavelet based image coding, the proposed scheme achieves more than 10% at bit rates higher than 0.3 bits/pixel over the conventional lossless coding method, and yields more improvement as bit rate becomes higher.

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An Effective Eye Location for Face Recognition (얼굴 인식을 위한 효과적인 눈 위치 추출)

  • Jung Jo Nam;Rhee Phill Kyu
    • The KIPS Transactions:PartB
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    • v.12B no.2 s.98
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    • pp.109-114
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    • 2005
  • Many researchers have been interested in user authentication using biometric information, and face recognition is a lively field of study of ones in the latest biometric recognition field because of advantage that it can recognize who he/she is without touching machinery. This paper proposes method to extract eye location effectively at face detection step that is precedence work of face recognition. The iterative threshold selection was adopted to get a proper binary image and also the Gaussian filter was used to intensify the properties of eyes to extract an eye location. The correlation was adopted to verify if the eye location is correct or not. Extraction of an eye location that propose in paper as well as accuracy, considered so that may can apply to online system and showed satisfactory performance as result that apply to on line system.

Shape Based Image Retrieval using Fourier Series (퓨리에 시리즈를 사용한 외형기반 이미지 검색)

  • Tak, Yoon-Sik;Hwang, Een-Jun
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10a
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    • pp.366-371
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    • 2006
  • 퓨리에 시리즈를 사용하면 이미지의 외곽선 특성을 표현할 수 있다. 이미지의 퓨리에 계수를 추출하기 위해서는 우선 이미지를 구성하는 주요 오브젝트를 표현하는 곡선을 추출한다. 이러한 곡선은 오브젝트의 특정 중심점에서 외곽선을 따라 일회전하면서 그 거리를 좌표상에 표시함으로써 얻을 수 있다. 기존의 퓨리에 계수를 추출하는 방법들은 추출된 계수를 이용하여 해당 곡선을 복원했을 때 원래의 곡선에 존재하던 상세한 특성을 표현하지 못한다는 단점이 있으며 이는 결국 이미지로부터 추출한 곡선을 사용하여 이미지를 검색할 때 정확도를 상당히 떨어뜨리게 한다. 이러한 문제점을 해결하기 위해서 본 논문에서는 Binary Range Reduction (BRR) 알고리즘을 제안한다. BRR 알고리즘은 원래의 곡선과 퓨리에 계수를 통해서 복원된 곡선간의 차이를 줄이기 위해서 전체의 곡선을 통해서 하나의 퓨리에 계수 세트를 추출하지 않고, 복원된 곡선이 원래의 곡선과 차이가 일정 크기 이상 나지 않도록 퓨리에 계수를 추출하는 구간을 나누어가며 퓨리에 계수를 추출한다. 이렇게 추출된 다수의 퓨리에 계수 세트를 통해서 복원된 곡선을 사용하여 이미지들 간의 유사도를 비교한다. 실험을 통하여 BRR 알고리즘을 사용하여 곡선에서 추출한 퓨리에 계수로 복원한 곡선이 원래 곡선의 특성을 정확하게 표현하고 있음을 보였고, 퓨리에 계수와 BRR알고리즘을 이미지 검색에 적용하였을 때, 높은 검색 결과를 얻을 수 있음을 보였다.

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Experimental Analysis of Equilibrization in Binary Classification for Non-Image Imbalanced Data Using Wasserstein GAN

  • Wang, Zhi-Yong;Kang, Dae-Ki
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.4
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    • pp.37-42
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    • 2019
  • In this paper, we explore the details of three classic data augmentation methods and two generative model based oversampling methods. The three classic data augmentation methods are random sampling (RANDOM), Synthetic Minority Over-sampling Technique (SMOTE), and Adaptive Synthetic Sampling (ADASYN). The two generative model based oversampling methods are Conditional Generative Adversarial Network (CGAN) and Wasserstein Generative Adversarial Network (WGAN). In imbalanced data, the whole instances are divided into majority class and minority class, where majority class occupies most of the instances in the training set and minority class only includes a few instances. Generative models have their own advantages when they are used to generate more plausible samples referring to the distribution of the minority class. We also adopt CGAN to compare the data augmentation performance with other methods. The experimental results show that WGAN-based oversampling technique is more stable than other approaches (RANDOM, SMOTE, ADASYN and CGAN) even with the very limited training datasets. However, when the imbalanced ratio is too small, generative model based approaches cannot achieve satisfying performance than the conventional data augmentation techniques. These results suggest us one of future research directions.

Barriers to Access Formal Financial Services: An Empirical Study from Indonesia

  • JAYANTI, Ari Dwi;AGUSTI, Kemala Sari;SETIYAWATI, Yuli
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.11
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    • pp.97-106
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    • 2021
  • The condition of financial services in Indonesia is unique, based on various characteristics, behaviors, and preferences. Therefore, the study of finance and banking is interesting to study as a recommendation for government policies. This paper aims to analyze the barriers to accessing formal financial services in Indonesia and why informal financial services are preferred. This paper presents a case study of financial inclusion in selected provinces in Indonesia using the SOFIA dataset from the Ministry of National Development Planning. Overall, this data consists of 20,000 individuals from 4 provinces and 93 regions representing the population in eastern Indonesia. The analysis was carried out by processing individual-level cross-sectional data surveyed in 2017 using the probit binary logistic method. The results identify the individual barriers in accessing formal financial services, including account ownership, saving, and credit activities in the formal financial institutions, and amplify the image by analyzing what determinants affect people to choose informal institutions. We found that some individual characteristics such as age, gender, education, income, employment status, residence, and access to technology significantly affect the barrier to formal financial services in East Indonesia.

Trends in Unikernel and Its Application to Manycore Systems (유니커널의 동향과 매니코어 시스템에 적용)

  • Cha, S.J.;Jeon, S.H.;Ramneek, Ramneek;Kim, J.M.;Jeong, Y.J.;Jung, S.I.
    • Electronics and Telecommunications Trends
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    • v.33 no.6
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    • pp.129-138
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    • 2018
  • As recent applications are requiring more CPUs for their performance, manycore systems have evolved. Since existing operating systems do not provide performance scalability in manycore systems, Azalea, a multi-kernel based system, has been developed for supporting performance scalability. Unikernel is a new operating system technology starting with the concept of a library OS. Applying unikernel to Azalea enables an improvement in performance. In this paper, we first analyze the current technology trends of unikernel, and then discuss the applications and effects of unikernel to Azalea. Azalea-unikernel was built in a single image consisting of libOS, runtime libraries, and an application, and executed with the desired number of cores and memory size in bare-metal. In particular, it supports source and binary compatibility such that existing linux binaries can be rebuilt and executed in Azalea-unikernel, and already built binaries can be run immediately without modification with a better performance. It not only achieves a performance enhancement, it is also a more secure OS for manycore systems.