The fact that the signature is widely used as a means of personal verification emphasizes the need for an automatic verification system because of the unfortunate side-effect of being easily abused by those who would feign the identification or intent of an individual. A great deal of work has been done in the area of off-line signature verification over the past few decades. Verification can be performed either Offline or Online based on the application. Online systems use dynamic information of a signature captured at the time the signature is made. Offline systems work on the scanned image of a signature. In this paper, we present a method for Offline Verification of signatures using a set of simple shape based geometric features. The features that are used are Area, Center of gravity, Eccentricity, Kurtosis and Skewness. Before extracting the features, preprocessing of a scanned image is necessary to isolate the signature part and to remove any spurious noise present. The system is initially trained using a database of signatures obtained from those individuals whose signatures have to be authenticated by the system. The details of preprocessing as well as the features depicted above are described throughout the discussion. Then artificial neural network (ANN) was used to verify and classify the signatures: exact or forged, and a classification ratio of about 93% was obtained under a threshold of 90%.The implementation details and simulation results are discussed in the thesis.

Abstract-Predicting the potential behavior a forest fire is an essential task in fire management which aims to minimize the negative impact of fire on property and society. Many fire spread models were developed. They are either physics-based or empirical models. These mathematical models usually use a set of non-linear equations which are mostly complex and couldn't easily applied in developing countries like Lebanon. This paper poses a semi-empirical mathematical model referring to the experimental results used in Anderson's model (1983) and relying on Rothermel's model (1972). The proposed equation uses parameters of both weather and topography, where wind speed and direction, fuel moisture content and slope coefficient are introduced to obtain the expected spread rate (mile/hour).This proposed model is characterized by its simplicity and thus the possibility of implementation in Lebanon.Index Terms-Fire spread rate, fuel moisture content, angle and slope coefficients.

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