Problem statement: Many approaches have been proposed in previous such as the classic sequential connected components labeling algorithm which is relies on two subsequent raster-scans of a binary image. This method produced good performance in terms of accuracy, but because of the implementation of the image processing systems now requires faster process of the computer, the speed of this techniques process has become an important issue. Approach: A computational approach, called components neighbors-scan labeling algorithm for connected component labeling was presented in this study. This algorithm required scanning through an image only once to label connected components. The algorithm started by scanning from the head of the components group, before tracing all the components neighbors by using the main components information. This algorithm had desirable characteristics, it is simple while promoted accuracy and low time consuming. By using a table of components, this approach also gave other advantages as the information for the next higher process. Results: The approach had been tested with a collection of binary images. In practically all cases, the technique had successfully given the desired result. Averagely, from the results the algorithm increased the speed around 67.4% from the two times scanning method. Conclusion: Conclusion from the comparison with the previous method, the approach of components neighbors-scan for connected component labeling promoted speed, accuracy and simplicity. The results showed that the approach has a good performance in terms of accuracy, the time consumed and the simplicity of the algorithm
<p>A random number can be defined as a set of numbers produced by a numerical function, in which the next number is unpredictable and a relationship between successive occurrences is lacking. Moreover, these sequences cannot be reproduced unless the same generator function with an exact initial value is used. The design of a random number generator must overcome the previous problems of a low periodic and the capacity to reproduce the same sequence. This paper proposes the knight tour as a tool for generating pseudo random numbers. These random numbers can be use in the encryption process or in a password generator for network administrators. The randomness test suite is used to ensure the randomness of outcome sequences. Roughly, 75% of the test results obtained is better than the results from other works. The statistical properties and security analysis indicate that the knight tour application is highly successful in generating a pseudo random number with good statistical results, high linear complexity and strong capacity to withstand attacks.</p>
Signature verification is defined as one of the biometric identification method using a person’s signature characteristics. The task of verifying the genuineness of a person signature is a complex problem due to the inconsistencies in the person signatures such as slant, strokes, alignment, etc. Too many features may decrease the False Rejection Rate (FRR) but also increases the False Acceptance Rate (FAR). A low value of FAR and FRR are required to obtain accurate verification result. There is a need to select the best features set of the signatures attributes among them. A combination of the current global features with four new features will be proposed such as horizontal distance, vertical distance, hypotenuse distance and angle. However, the value of FAR may increase if too many features are used which result a slow verification performance. In order to select the best features, the difference between the mean of the standard deviation ratio of each feature will be used. The main objective is to increase the accuracy of verification rate. This can be determined using best features set selected during the features selection process. A selection of signature set with strong feature sets will be used as a control parameter. The parameter is then used to validate the results.
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