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High-frequency energy distributions are important characteristics of blurry images. In this paper, directional high-pass filters are proposed to analyze blurry images. Firstly, we show that the proposed directional high-pass filters can effectively estimate the motion direction of motion blurred images. A closed-form solution for motion direction estimation is derived. It achieves a higher estimation...
Super-resolution reconstruction produces high-resolution images from a set of low-resolution images of the same scene. In the last two and a half decades, many super-resolution algorithms have been proposed. These algorithms are very sensitive to their assumed models of motion and noise, and computationally expensive for many practical applications. In this paper we adopt earlier reported fast prediction...
Multi-instance learning (MIL) is a variational supervised learning. Instead of getting a set of instances that are labeled, the learner receives a set of bags that are labeled. Each bag contains many instances. In this paper, we present a novel MIL algorithm that can efficiently learn classifiers in a large instance space. We achieve this by estimating instance distribution using a proposed extended...
Recently, object tracking has been widely studied as a binary classification problem. Semi-supervised learning is particularly suitable for improving classification accuracy when large quantities of unlabeled samples are generated (just like tracking procedure). The purpose of this paper is to fulfill robust and stable tracking by using collaborative learning, which belongs to the scope of semi-supervised...
Face recognition in unconstrained, natural conditions still remains a challenging task. As a powerful local descriptor, Local Binary Patterns has shown the advantage of representation and performance. However, it is still affected by robustness and accuracy. In this paper, a novel method is presented to improve the performance of automatic face recognition under uncontrolled conditions. We modify...
Border Gateway Protocol (BGP) is the de-facto inter-domain routing protocol used across thousands of Autonomous Systems (AS) joined together in the Internet. Security has been a major issue for BGP. Nevertheless, BGP suffers from serious threats even today, like Denial of Service (DoS) attack and misconfiguration of routing information. BGP is one of the complex routing protocols and hard to configure...
Radio-frequency identification (RFID) is an automatic identification system which has become a hot topic in the fields of manufacturing, logistics, and so on. The purpose of this research is to propose a methodology for designing the RFID network planning problem (RNP) for application in the Mackay Memorial Hospital in Hsinchu, Taiwan. In this study, the RFID network is first considered as a grid...
Cloud computing plays an important role in current converged networks. It brings convenience of accessing services and information to users regardless of location and time. However, there are some critical security issues residing in cloud computing, such as availability of services. Denial of service occurring on cloud computing has even more serious impact on the Internet. Therefore, this paper...
Removing noise from a digital image is a challenging problem. Application of Gaussian Scale Mixtures (GSM) in the wavelet domain has been reported to be one of the most effective denoising algorithms, published to date. The performance of this algorithm depends on the chosen wavelet representation. In this paper, we introduce an improved wavelet pyramid representation based on the Battle-Lemarie wavelet...
One of the major objectives in multimedia research is to provide pervasive access and personalized use of multimedia information. Pervasive access of video data implies the access of cognitive and affective aspects of video content. Personalized use requires the services satisfy individual user's needs on video content. This article attempts to provide a content-on-demand (CoD) video adaptation solution...
Movie shot classification is vital but challenging task due to various movie genres, different movie shooting techniques and much more shot types than other video domain. Variety of shot types are used in movies in order to attract audiences attention and enhance their watching experience. In this paper, we introduce context saliency to measure visual attention distributed in keyframes for movie shot...
Removing noise from a digital image is a challenging problem. Application of Gaussian Scale Mixtures (GSM) in the wavelet domain has been reported to be one of the most effective denoising algorithms, published to date. In this paper we investigate the impact of overcomplete wavelet image representations on the GSM image denoising algorithm. We explore the desirable local characteristics of wavelet...
This paper proposes an image clustering algorithm using Particle Swarm Optimization (PSO) with two improved fitness functions. The PSO clustering algorithm can be used to find centroids of a user specified number of clusters. Two new fitness functions are proposed in this paper. The PSO-based image clustering algorithm with the proposed fitness functions is compared to the K-means clustering. Experimental...
Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct...
Anomaly Intrusion Detection System (IDS) is a statistical based network IDS which can detect attack variants and novel attacks without a priori knowledge. Current anomaly IDSs are inefficient for real-time detection because of their complex computation. This paper proposes a novel approach to reduce the heavy computational cost of an anomaly IDS. Linear Discriminant Analysis (LDA) and difference distance...
In this paper an improved hill climbing algorithm based method is presented to cut character out of the license plate images. Although there are many existing commercial LPR systems, with poor illumination conditions and moving vehicle the accuracy impaired. After examination and comparison of two different types of image segmentation approaches, the hill climbing algorithm based method gave a better...
Many machine learning tasks can be achieved by using Multiple-instance learning (MIL) when the target features are ambiguous. As a general MIL framework, Diverse Density (DD) provides a way to learn those ambiguous features by maxmising the DD estimator, and the maximum of DD estimator is called a concept. However, modeling and finding multiple concepts is often difficult especially without prior...
This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance...
Human detection has been widely used in many applications. In the meantime, it is still a difficult problem with many open questions due to challenges caused by various factors such as clothing, posture and etc. By investigating several benchmark methods and frameworks in the literature, this paper proposes a novel method which successfully implements the Real AdaBoost training procedure on multi-scale...
In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our...
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