Digital Commons Network^™

A Pipeline For Structured Light Bathymetric Mapping, Gabrielle Inglis, Clara Smart, J. Vaughn, Chris Roman

Christopher N. Roman

This paper details a methodology for using structured light laser imaging to create high resolution bathymetric maps of the sea floor. The system includes a pair of stereo cameras and an inclined 532nm sheet laser mounted to a remotely operated vehicle (ROV). While a structured light system generally requires a single camera, a stereo vision set up is used here for in-situ calibration of the laser system geometry by triangulating points on the laser line. This allows for quick calibration at the survey site and does not require precise jigs or a controlled environment. A batch procedure to extract the …

In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as …

Building A Simulation Platform For Chinese Calligraphy Characters, Chung-Shing Wang, Teng-Ruey Chang, Man-Ching Lin, Ya-Hui Wang

DRS Biennial Conference Series

This research looked at an existing Chinese calligraphy font, the Kai-font, and carried out geometric modeling and analysis to set up a stroke feature model database. This allowed creation of an independent calligraphy simulation platform for extracting and analyzing fonts. Users can then input through the use of a mouse, digit pad or other systems to draw out the strokes of a Chinese character. The system will then automatically recognize the stroke starting coordinates, angles, area ratio and other parameters for stroke feature analysis and extraction. These data can then be compared with stroke feature information in the database to …

A Pollution Attack To Public-Key Watermarking Schemes, Yongdong Wu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Public-key watermarking schemes are required to possess two desirable properties: allowing everyone to determine whether a watermark exists in an image or not and ensuring high detection probability in case of malicious modification. In this paper we propose an attack which pollutes the watermark embedded in an image with an optimal colored noise so as to fool the detector of the underlying public-key watermarking scheme. We further show how to apply the proposed pollution attack to public-key subspace watermarking schemes to generate pirated images of high quality but of low detection probability. Our experiment results demonstrate that the proposed pollution …

Modeling Spatial Uncertainties In Geospatial Data Fusion And Mining, Boris Kovalerchuk, Leonid Perlovsky, Michael Kovalerchuk

All Faculty Scholarship for the College of the Sciences

Geospatial data analysis relies on Spatial Data Fusion and Mining (SDFM), which heavily depend on topology and geometry of spatial objects. Capturing and representing geometric characteristics such as orientation, shape, proximity, similarity, and their measurement are of the highest interest in SDFM. Representation of uncertain and dynamically changing topological structure of spatial objects including social and communication networks, roads and waterways under the influence of noise, obstacles, temporary loss of communication, and other factors. is another challenge. Spatial distribution of the dynamic network is a complex and dynamic mixture of its topology and geometry. Historically, separation of topology and geometry …

Character-Based Automated Human Perception Quality Assessment In Document Images, Tayo Obafemi-Ajayi, Gady Agam

Electrical and Computer Engineering Faculty Research & Creative Works

Large degradations in document images impede their readability and deteriorate the performance of automated document processing systems. Document image quality (IQ) metrics have been defined through optical character recognition (OCR) accuracy. Such metrics, however, do not always correlate with human perception of IQ. When enhancing document images with the goal of improving readability, e.g., in historical documents where OCR performance is low and/or where it is necessary to preserve the original context, it is important to understand human perception of quality. The goal of this paper is to design a system that enables the learning and estimation of human perception …

Mcnamara 2011 Feature Extraction (Image Analysis), George Mcnamara

George McNamara

Feature Extraction presentation and movies in a ZIP file from a presentation I gave at ISAC 2011 in Baltomore, Md.

Feature extraction is one phrase for image analysis.

Hybrid Feature Selection For Text Classification, Serkan Günal

Turkish Journal of Electrical Engineering and Computer Sciences

Feature selection is vital in the field of pattern classification due to accuracy and processing time considerations. The selection of proper features is of greater importance when the initial feature set is considerably large. Text classification is a typical example of this situation, where the size of the initial feature set may reach to hundreds or even thousands. There are numerous research studies in the literature offering different feature selection strategies for text classification, mostly focused on filters. In spite of the extensive number of these studies, there is no significant work investigating the efficacy of a combination of features, …

Abstract Feature Extraction For Text Classification, Göksel Bi̇ri̇ci̇k, Banu Di̇ri̇, Ahmet Coşkun Sönmez

Turkish Journal of Electrical Engineering and Computer Sciences

Feature selection and extraction are frequently used solutions to overcome the curse of dimensionality in text classification problems. We introduce an extraction method that summarizes the features of the document samples, where the new features aggregate information about how much evidence there is in a document, for each class. We project the high dimensional features of documents onto a new feature space having dimensions equal to the number of classes in order to form the abstract features. We test our method on 7 different text classification algorithms, with different classifier design approaches. We examine performances of the classifiers applied on …

Graphical Image Classification Combining An Evolutionary Algorithm And Binary Particle Swarm Optimization, Beibei Cheng, Renzhong Wang, Sameer K. Antani, R. Joe Stanley, George R. Thoma

Electrical and Computer Engineering Faculty Research & Creative Works

Biomedical journal articles contain a variety of image types that can be broadly classified into two categories: regular images, and graphical images. Graphical images can be further classified into four classes: diagrams, statistical figures, flow charts, and tables. Automatic figure type identification is an important step toward improved multimodal (text + image) information retrieval and clinical decision support applications. This paper describes a feature-based learning approach to automatically identify these four graphical figure types. We apply Evolutionary Algorithm (EA), Binary Particle Swarm Optimization (BPSO) and a hybrid of EA and BPSO (EABPSO) methods to select an optimal subset of extracted …

Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Many techniques have been recently developed for classification of hyperspectral images (HSI) including support vector machines (SVMs), neural networks and graph-based methods. To achieve good performances for the classification, a good feature representation of the HSI is essential. A great deal of feature extraction algorithms have been developed such as principal component analysis (PCA) and independent component analysis (ICA). Sparse coding has recently shown state-of-the-art performances in many applications including image classification. In this paper, we present a feature extraction method for HSI data motivated by a recently developed sparse coding based image representation technique. Sparse coding consists of a …