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In this paper, we introduce an alpha-numerical sequences extraction system (keywords, numerical fields or alpha-numerical sequences) in unconstrained handwritten documents. Contrary to most of the approaches presented in the literature, our system relies on a global handwriting line model describing two kinds of information : i) the relevant information and ii) the irrelevant information represented...
The BP Deepwater Horizon oil spill disaster has reminded us, once again, the potential for systemic failures in complex engineered systems. But such systemic failures are not limited to the chemical and petrochemical industries alone. The 2003 Northeast electrical power blackout was a systemic failure. Financial disasters such as Enron, WorldCom, subprime derivatives market, and so on, also belong...
In this paper, Human Visual System (HVS) characteristics are modeled using Lee and Lu's Fuzzy- BP network for the purpose of image watermarking. The Fuzzy-BP network is trained by 27 inference rules comprising of three input HVS features namely luminance sensitivity, edge sensitivity computed using threshold and contrast sensitivity computed using variance. The Fuzzy-BP network block wise produces...
Rapid increase of the amount of image data necessitates the development of efficient tools for representing visual input. In this paper, we present an approach for automatically extracting the ROI (region of interest) and that can find objects using visual attention technique. Multiple image features such as intensity, color and orientation in multiple scales are extracted to get some feature maps...
The wood cells properties determine the physical properties of the wood. This paper analyzes the digital characteristics of the wood cells. After some analysis, this paper puts forward the recognition approach of timber species on the basis of mathematical simulation theory and establishes a hexagon mathematics model for wood cells. Various parameters have been extracted and obtained, namely area,...
Speech recognition (i.e. speech to text conversion)and speech synthesis (i.e. text to speech conversion)are two main operations performed in human computer interaction through natural language conversational interface. This paper presents a novel approach for modeling and designing of a Hindi speech recognition system, by using Perceptual Linear Prediction (PLPRASTA)for feature extraction and Gaussian...
In this paper we tackle the problem of detecting individual human actions in video sequences. While the most successful methods are based on local features, which proved that they can deal with changes in background, scale and illumination, most existing methods have two main shortcomings: first, they are mainly based on the individual power of spatio-temporal interest points (STIP), and therefore...
This paper presents a novel approach for unexpected behavior recognition in image sequences with attention to high density crowd scenes. Due to occlusions, object-tracking in such scenes is challenging and in cases of low resolution or poor image quality it is not robust enough to efficiently detect abnormal behavior. The wide variety of possible actions performed by humans and the problem of occlusions...
Image matting is the process of extracting a foreground element from a single image with limited user input. To solve the inherently ill-posed problem, there exist various methods which use specific color model. One representative method assumes that the colors of the foreground and background elements satisfy the linear color model. The other recent method considers line-point color model and point-point...
A method to classify tentative feature matches as inliers or outliers to a transformation model is presented. It is well known that ratios of areas of corresponding shapes are affine invariants. Our algorithm uses consistency of ratios of areas in pairs of images to classify matches as inliers or outliers. The method selects four matches within a region, and generates all possible corresponding triangles...
In this paper we propose a new framework for view-invariant 3D object recognition, based on what we call Visibility Maps. A Visibility Map (VM) encodes a compact model of an arbitrary 3D object for which a set of images taken from different views is available. Representative local invariant features extracted from each image are selectively combined to form a visibility basis, in terms of which an...
Surrogate models of fitness have been presented as a way of reducing the number of fitness evaluations required by an evolutionary algorithm. This is of particular interest with expensive fitness functions where the cost of building the model is outweighed by the saving of using fewer function evaluations. In this paper we show how a Markov network model can be used as a surrogate fitness function...
One of the key elements of the data integration process is conflation of spatial data from two different sources, which results in a single data set that incorporates data and attributes from both sources. Registration techniques needed for conflation can be rigid or non-rigid, depending on the underlying transformation. A key characteristic of rigid transformation is that all distances are preserved.
This work presents an unconstrained offline hand-written line recognition system based on hybrid HMM (Hidden Markov Model)/ANN (Artificial Neural Network) models. The particularity of the system lies in the use of an ensemble of connectionist/statistical character n-gram language models. These language models are trained with a text corpus at character level; therefore, no explicit lexicon is used...
In this paper we develop a model which, through a dynamic modulatory local feedback mechanism, is capable of categorizing multiple simultaneously-presented input patterns while only previously being trained on single patterns. The key process is shown to be segmentation where low level feature detectors are grouped with their corresponding high level categories. While most existing approaches use...
In this paper, an approach named isovolume extraction for 3D Data Sets rendering is presented. This approach extracts and visualizes a model that meets the desired range property values. It extends previous visualization techniques and is very suitable for closed objects extraction. After deeply studying the centroid-based isovolume extraction algorithm proposed by David J. Russomanno et.al, authors...
Visual recognition and detection are computationally intensive tasks and current research efforts primarily focus on solving them without considering the computational capability of the devices they run on. In this paper we explore the challenge of deriving methods that consider constraints on computation, appropriately schedule the next best computation to perform and finally have the capability...
In this paper we will present a geometric lane representation which enables a 4D-lane tracker to handle ambiguous, non-parallel and even crossing lane marking tracks in complex situations. The introduced geometry model contains lateral independent tracks which lie on top of the surface of a continuous shape that is formed like the road surface within a specific preview and is bent in horizontal, vertical...
In this paper, we present a new object matching algorithm based on linear programming and a novel locally affine-invariant geometric constraint. Previous works have shown possible ways to solve the feature and object matching problem by linear programming techniques. To model and solve the matching problem in a linear formulation, all geometric constraints should be able to be exactly or approximately...
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