Gravitational search algorithm (GSA) is a recent introduced global convergence guaranteed algorithm. In this paper, a quantum-behaved gravitational search algorithm, namely called as QGSA, is proposed. In the proposed...Gravitational search algorithm (GSA) is a recent introduced global convergence guaranteed algorithm. In this paper, a quantum-behaved gravitational search algorithm, namely called as QGSA, is proposed. In the proposed QGSA each individual mass moves in a Delta potential well in feasible search space with a center which is weighted average of all kbests. The QGSA is tested on several benchmark functions and compared with the GSA. It is shown that the quantum-behaved gravitational search algorithm has faster convergence speed with good precision, and thus generating a better performance.展开更多
One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is att...One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is attended. This paper proposes a method which can automatically detect eye in extensive range of images with different conditions. In the proposed method, first an image is enhanced by morphological operations then region of face is detected by hybrid projection function. To identify window of eye, vertical edge dominance map is used. The authors＇ method uses elliptical mask on eye image to detect center of pupil. The mask scans eye image to find minimum gray level because pupil is darkest part in eye image compared with 3 well-known methods. The accuracy of 99.53% on this This method has implemented on JAFFE face database and database confirms efficiency of the proposed method.展开更多
文摘Gravitational search algorithm (GSA) is a recent introduced global convergence guaranteed algorithm. In this paper, a quantum-behaved gravitational search algorithm, namely called as QGSA, is proposed. In the proposed QGSA each individual mass moves in a Delta potential well in feasible search space with a center which is weighted average of all kbests. The QGSA is tested on several benchmark functions and compared with the GSA. It is shown that the quantum-behaved gravitational search algorithm has faster convergence speed with good precision, and thus generating a better performance.
文摘One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is attended. This paper proposes a method which can automatically detect eye in extensive range of images with different conditions. In the proposed method, first an image is enhanced by morphological operations then region of face is detected by hybrid projection function. To identify window of eye, vertical edge dominance map is used. The authors＇ method uses elliptical mask on eye image to detect center of pupil. The mask scans eye image to find minimum gray level because pupil is darkest part in eye image compared with 3 well-known methods. The accuracy of 99.53% on this This method has implemented on JAFFE face database and database confirms efficiency of the proposed method.
