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18th ieeE International colloquium on Signal processing and applications (CSPA)

作者： Ahmed, Ismail Taha Hammad, Baraa Tareq Jamil, Norziana Univ Anbar Coll Comp Sci & Informat Technol Anbar Iraq Univ Tenaga Nas Coll Comp & Informat Kajang Malaysia

ISBN: (纸本)9781665485296

the process of identifying the presence of secret information in cover images is known as image steganalysis. As a result, classifying an image as a cover image or a stego image might be considered a classification task. The majority of steganalysis approaches that rely on deep learning are effective. Deep learning technology can identify and extract features mechanically using deep networks, allowing steganalysis technology to eliminate the need for specialist knowledge. However, Deep learning model training is tough and takes a large amount of processing time and information. Therefore, pre-trained CNN such as AlexNet model were used as feature extractors to save time during training. Therefore, this research presented an image steganalysis method based on AlexNet CNN Model. There are 3 steps make up the proposed image steganalysis method: Firstly, Data collection and preparation. Secondly, AlexNet model are used for extract Distinctive features. Lastly, the feature vector is then utilized to train the Random forest (RF) classifier in order to detect the binary classification (Cover/Stego). The experimental results under IStego100K database show that the proposed method accuracy is 99%. The properties of AlexNet models can be deduced to be useful and concise to classify using RF. In compared to previous techniques, the presented method outperformed them.

关键词： image Steganalysis CNN AlexNet CNN Model Random forest (RF) Classifier IStego100K

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Improve Black Ice image Detection for Road Safety

Improve Black Ice Image Detection for Road Safety

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International colloquium on Signal processing & Its applications, CSPA

作者： Falah Amer Abdulazeez Ismail Taha Ahmed Baraa Tareq Hammad College of Education Pure Sciences University of Anbar Anbar Iraq College of Computer Sciences and Information Technology University of Anbar Anbar Iraq

ISBN: (数字)9798331522193

ISBN: (纸本)9798331522209

A tiny amount of Black Ice that mixtures in into the road's surface is frequently clear or virtually undetectable. In order to detect the existence of black ice on roads, a variety of sensors, algorithms, and methods are used. Black ice detection is essential, particularly for car navigational systems and safety on the roads. The purpose of the research is to propose black ice detection method based on a combination of global and local texture features, such as grey level co-occurrence matrix (GLCM) and Local binary Patterns (LBP), to capture both overall patterns and fine details. The proposed method is divided into four phases: image preprocessing comes first, followed by texture feature extraction techniques like GLCM and LBP. Use the relief approach to choose the best feature. Two classifiers, linear discriminant analysis (LDA) and DT, are used to distinguish between images with and without black ice. There isn't a large collection of black ice images that can be used for this research. Consequently, the black ice image data required for the training was obtained through Google image search. According to the findings of the experiments, the proposed GLCM-LBP-LDA attained an accuracy rate of 95%, surpassing the overall accuracy of the most current techniques now in use.

关键词： Training Accuracy Navigation Feature extraction Ice Road safety Sensors Safety Linear discriminant analysis Reliability

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Handwriting Detection and Recognition Improvements Based on Hidden Markov Model and Deep Learning

Handwriting Detection and Recognition Improvements Based on ...

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International colloquium on Signal processing & Its applications, CSPA

作者： Mohammed Hazim Alkawaz Cheng Chun Seong Husniza Razalli Faculty of Information Sciences & Engineering Management and Science University Shah Alam Selangor Malaysia School of Graduates Studies Management and Science University Shah Alam Selangor Malaysia

ISBN: (数字)9781728153100

ISBN: (纸本)9781728153117

The online handwriting detection and recognition has become an important research in ... area. An individual's writing can be easily forged and disguised in various ways including freehand simulation, tracing and image transfer, making genuine handwriting recognition a challenging task. With the advent of various online handwriting recognition systems developed, but for English characters recognition these still lack the simplicity and accuracy. While identification approaches were successfully reported, good forgeries are able to outsmart the existing tools. Existing flaws in recognition systems led to more research works in automatic detection and recognition works via computer techniques, feature extraction, classification accuracy comparison, performance evaluation and pattern recognition. To realize simpler and efficient English character recognition, we develop a handwriting detection and recognition system based on the Kohonen Network and deep learning. The system consists of interfaces for the online handwritten character was featured in matrix form of sizes 5x7 pixel and 35x33 pixels represented with binary values. Identifying all occupied character strokes in the series of binary string recognizes the full character. The recognition performance was compared between 35 pixels and 1155 pixels environment, evaluated in terms of accuracy, and consistency. An experiment was conducted with 25 online handwritten input data of straight stroke (' `V', ' `X', ' `Y') and curve stroke (' `C', ' `O', ' `S') characters collected from 25 participants. Findings show an overall improvement of 31 % recognition accuracy of using 35x33 pixels against the 5x7 pixels. Handwriting characters featured in 35x33 pixels outperformed the 5x7 pixels accuracy by 37.49% on straight stroke characters and 24.52 % on curve stroke.

关键词： Character recognition Handwriting recognition Hidden Markov models Feature extraction Signal processing Machine learning Optical character recognition software

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SITD and across-bin matching for deformed images acquired by scanners

SITD and across-bin matching for deformed images acquired by...

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International colloquium on Signal processing & Its applications, CSPA

作者： Omar M Wahdan Mohammad Faidzul Nasrudin Khairuddin Omar Centre for Artificial Intelligence Technology UKM Bangi Selangor Malaysia

In this paper, a Shearing Invariant Texture Descriptor (SITD) is presented and the across-bin matching techniques Quadratic Distance (QD) and the Earth Movers Distance (EMD) are used. The shearing and 180° rotation are the main deformations generated during the image acquisition process from the physical paper using scanners. It is very common that a sheet of paper is placed imperfectly on the scanner, whereas the slight rotation is usually not based on the paper geometrical center. The acquired image therefore deformed with irregular rotation which produces a shearing transform. Besides, the image can easily be scanned upside down when the query image is acquired. This problem produces an images deformed with 180° rotation. The SITD is only invariant to the shearing transform and the 180° rotation turning positions of the extracted features. Thus, using the ordinary bin-by-bin matching techniques result in incorrect matches to the corresponding features. Hence, we proposed to use the across-bin matching techniques to perfectly match the features. The experimental results showed the superiority of the SITD along with QD when compared to the benchmark methods Local binary Pattern (LBP) and Shearing Moment Invariant (SMI) descriptors. Besides, in most cases the QD outperformed the EMD and showed a reasonable performance.

关键词： Shearing Feature extraction Fingerprint recognition Earth Histograms Vectors Signal processing

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binary shape coding using finite automata

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iee PROCEEDINGS-VISION image AND SIGNAL processing 2006年第5期153卷 695-702页

作者： Makarov, A. Moniri, M. Staffordshire Univ Fac Comp Engn & Technol Stoke On Trent ST18 0DF Staffs England

Two new binary shape-coding techniques that are based on finite automata methods are proposed. Both contour-based and bitmap-based approaches to shape coding are investigated using one-dimensional-weighted finite automata (1D-WFA) and generalised finite automata (GFA) algorithms, respectively. We evaluate the fidelity of shape representation, using 1D-WFA and GFA methods in intraframe mode and compare the performance of the proposed coding techniques against each other and with the benchmark, context-based arithmetic encoding (CAE) of shapes used in MPEG-4. It is found that the GFA method is more suitable for video applications than 1D-WFA and therefore it is adapted to operate in interframe mode. More importantly, GFA is the first shape-coding technique reported to date that has the unique advantage of shape processing in the compressed domain. This is due to the fact that the shape representation in the compressed domain using GFA facilitates processing at the expense of less compression efficiency compared with MPEG-4 CAE. Moreover, shapes encoded using the GFA method can be decoded at any desirable resolution.

关键词： SHAPES CODING theory CELLULAR automata MPEG (Video coding standard) VIDEO compression

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Proceedings of the 1998 iee colloquium on Underwater applications of image processing

Proceedings of the 1998 IEE Colloquium on Underwater Applica...

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Proceedings of the 1998 iee colloquium on Underwater applications of image processing

The proceedings contains 12 papers from the iee colloquium on Underwater applications of image processing. Topics discussed include: sidescan sonar survey data analysis;underwater robotics navigation using multisensor fusion;behaviors implemented using a vision system based on coded light projection;broadband underwater acoustic communications systems;wide-band high-resolution sonar techniques;autonomous underwater vehicles as imaging platforms;automated acoustic data collection experiments using a directional projector system;uncalibrated computer vision techniques in the underwater environment;and underwater measurement of salmon biomass.

关键词： image processing

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Nonlinear and nonstationary signal processing

Nonlinear and nonstationary signal processing

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Proceedings of the 1998 iee colloquium on Non-Linear Signal and image processing

作者： Fitzgerald, W.J. Smith, R.L. Walden, A.T. Young, P.C.

A research program is conducted to unify existing methods of signal processing and to identify areas of research where new techniques are required. The focus of study includes nonlinear and nonstationary time series estimation, forecasting and changepoint modeling, nonlinear signal processing in econometrics and financial time series, dynamical systems, environmental applications and spatial data analysis, and applications of Bayesian signal processing. A discussion and experimentation of existing and new-developed technology are also included.

关键词： Signal processing

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image processing for underwater measurement of salmon biomass

Image processing for underwater measurement of salmon biomas...

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Proceedings of the 1998 iee colloquium on Underwater applications of image processing

作者： Chan, D. McFarlane, N. Hockaday, S. Tillett, R.D. Ross, L.G. Silsoe Research Inst Bedford United Kingdom

A non-intrusive method for monitoring salmon stock has been developed which includes the use of two matched monochrome CCD cameras. Stereo image sequences are grabbed and digitized. The images are used to calculate various measurements from the fish, which are then used to estimate its mass. Methods for estimating the fish mass have been investigated. An image analysis algorithm for locating salmon from an underwater image has been developed and more advanced techniques are under development.

关键词： image analysis

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Acoustic communications: Experimental data collection, image transmission, visualization, and speculation

Acoustic communications: Experimental data collection, image...

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Proceedings of the 1998 iee colloquium on Underwater applications of image processing

作者： Dunbar, Robin M. McHugh, Ronald Heriot-Watt Univ Edinburgh United Kingdom

Although optical and electromagnetic wave signaling techniques are useful in some specialized underwater applications, the most common form of information carrier for significant through-water distances is acoustic. To produce a communication system with particular range, depth and signal bandwidth requirements, the designer normally looks for an appropriate model from which to deduce operational details such as carrier frequency, modulation format, transmitter power and receiving array geometry. Experimental data on the validation of mathematical models for a variety of operational details are obtained from the European Experimentally Validated Models for Acoustic Channels project and discussed.

关键词： Underwater acoustics

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Uncalibrated computer vision techniques in the underwater environment

Uncalibrated computer vision techniques in the underwater en...

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Proceedings of the 1998 iee colloquium on Underwater applications of image processing

作者： Plakas, K. Trucco, E. Heriot-Watt Univ Edinburgh United Kingdom

Uncalibrated computer vision is a relatively new but fast growing area of computer vision research. Uncalibrated computer vision dispenses with the whole calibration procedure, extracting all the information it needs from the images themselves. It allows for greater versatility since no assumptions about the camera setup are made, and greater robustness since one possible source of error is eliminated. Early results of the application of uncalibrated computer vision techniques in the underwater environment are presented. The robustness and versatility of the techniques are demonstrated through synthetic data and real underwater sequences.

关键词： Computer vision

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