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The current trend of growth of information reveals that it is inevitable that large-scale learning problems become the norm. In this paper, we propose and analyze a novel Low-density Cut based tree Decomposition method for large-scale SVM problems, called LCD-SVM. The basic idea here is divide and conquer: use a decision tree to decompose the data space and train SVMs on the decomposed regions. Specifically,...
The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalities and draw correct diagnosis is vital. We experimented with wavelet and Local Energy based Shape Histogram (LESH) features combined with Echo State Network classifier. The suggested...
In this preliminary research we examine the suitability of hierarchical strategies of multi-class support vector machines for classification of induced pluripotent stem cell (iPSC) colony images. The iPSC technology gives incredible possibilities for safe and patient specific drug therapy without any ethical problems. However, growing of iPSCs is a sensitive process and abnormalities may occur during...
As one tool for structuring a massive volume of archived news videos based on their semantic contents, this paper proposes a method to detect scene duplicates from news videos. A scene duplicate is a pair of video segments taken at the same event from different viewpoints. Referring to the audio channel is effective to detect scene duplicates regardless of viewpoints, but it cannot be relied on when...
The histogram specification turns a shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of specification drops because of quantization error...
Recognition of offline musical symbols can aid in automatic retrieval of a particular piece of musical notation from a digital repository. Though some work on on-line Musical symbol notations exists, little work has been done on off-line recognition of the symbols. This article proposes a system for offline isolated musical symbol recognition. Efficacy of a texture analysis based feature extraction...
In this study, we have proposed an improvement for feature extraction in computer-aided diagnosis (CAD) system for colorectal endoscopic images with narrow-band imaging (NBI) magnification. Dense Scale-Invariant Feature Transform (D-SIFT) is used in the feature extraction. It is necessary to consider a trade-off between the precision of the feature extraction and speedup by the FPGA implementation...
Palmprint is a reliable and unique biometric trait with high acceptability. In this paper, we propose a new Local Composition Derivative Pattern (LCDP) for palmprint recognition. LCDP extracts first order derivative information of images along radial and directional directions which can capture more detailed information than the non-directional local binary pattern (LBP). Different from LBP encoding...
Stitching images with repeated patterns is one of the hard tasks in computer vision. Unfortunately, available algorithms do not have enough accuracy to register these kinds of images. This problem is due to lack of discriminative information of corresponding points of images. To overcome this shortcoming, a novel method for feature-based image stitching is proposed. In the proposed method, the SIFT...
As digital video databases grow, so grows the problem of effectively navigating through them. In this paper we propose a novel content-based video retrieval approach to searching such video databases, specifically those involving human actions, incorporating spatio-temporal localization. We outline a novel, highly efficient localization model that first performs temporal localization based on histograms...
Matching one document with other documents is one of anti-plagiarism tasks. Matching can be performed both intra and extra-corpal. This paper will discuss extra-corpal matching utilize the web crawlers as reference search. The role of web-crawler described in extra-corpal anti-plagiarism architecture. Matching of plagiarism indication will use Modified Histogram Intersection based on N-Gram of term...
The goal of the paper is to predict student retention by using linear discriminant analysis with bootstrapping. The result (93%) provides accuracy superior to the bootstrapping of a comparative method, as well as to the non-bootstrapping variations. In order to perform discriminant analysis, we linearize a fractional programming method by using Charnes-Cooper transformation and apply linear programming,...
Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper presents a method to separate the textual and non textual components in document images using a graph-based modeling and...
Local Binary Pattern (LBP) has been well recognised and widely used in various texture analysis applications of computer vision and image processing. It integrates properties of texture structural and statistical texture analysis. LBP is invariant to monotonic gray-scale variations and has also extensions to rotation invariant texture analysis. In recent years, various improvements have been achieved...
Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper presents a method to separate the textual and non textual components in document images using a graph-based modeling and...
Significant documents or old scarce books have been saved in digital forms by scanning. However, some noises may occur in a scanned image such as marginal noises. The marginal noises usually appear as dark regions around the margin of the scanned documents. In this paper, we propose a method for removing marginal noise by analyzing image histogram or projection profile of the document image. The method...
Retrieving book covers in web images or in specified database has a wide application prospect, from electronic commerce to picture search. We describe a book cover retrieval system based on enhanced SIFT descriptor by incorporating “binary string” descriptor. Furthermore, a new error recovery based on angle difference of the matching pairs is integrated into the SIFT matching method. Experiments demonstrate...
This paper presents the results of the first eye movement verification and identification competition. The work provides background, discusses previous research, and describes the datasets and methods used in the competition. The results highlight the importance of very careful eye positional data capture to ensure meaningfulness of identification outcomes. The discussion about the metrics and scores...
As the performance of predictor is crucial to prediction-error based reversible data hiding, this study investigates a predictor using the least-square method to improve the prediction accuracy. The proposed predictor uses a checkerboard division to partition an image into two disjoint sets. One set is predicted by the other set using the prediction weights obtained by least-square method. The histogram-shifting...
Classifier combination can be used to combine multiple classification decisions to improve object classification performance, and weighted average is a popular method for this purpose. In this paper we propose to use a graph-theoretic clustering method to define the weights for SVM classifier decisions. Specifically, we use the dominant set clustering to evaluate the difficulty of a kernel matrix...
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