In this paper human face machine identification is experienced using optical correlation techniques in spatial frequency domain. This approach is tested on ORL dataset of faces which includes face images of 40 subject...In this paper human face machine identification is experienced using optical correlation techniques in spatial frequency domain. This approach is tested on ORL dataset of faces which includes face images of 40 subjects, each in 10 different positions. The examined optical setup relies on optical correlation based on developing optical Vanderlugt filters and its basics are described in this article. With the limitation of face database of 40 persons, the recognition is examined successfully with nearly 100% of accuracy in matching the input images with their respective Vanderlugt synthesized filters. Software simulation is implemented by using MATLAB for face identification.展开更多
In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards...In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,etc.This new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power level.Compared to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization strategy.The key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis testing.We discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are presented.Numerical examples are provided to corroborate the proposed studies.展开更多
Gender recognition has gained more attention. However, most of the studies have focused on face images acquired under controlled conditions. In this paper, we investigate gender recognition on real-life faces. We prop...Gender recognition has gained more attention. However, most of the studies have focused on face images acquired under controlled conditions. In this paper, we investigate gender recognition on real-life faces. We proposed a gender recognition scheme, which is composed of four parts: face detection, median filter, feature extraction, and gender classifier. MULBP features are adopted and combined with a SVM classifier for gender recognition. The MULBP feature is robust to noise and illumination variations. In the experiment, we obtain 98.32% using LFW database and 97.30% on Samsung Gender dataset, which shows the superior performance in gender recognition compared with the conventional operators.展开更多
文摘In this paper human face machine identification is experienced using optical correlation techniques in spatial frequency domain. This approach is tested on ORL dataset of faces which includes face images of 40 subjects, each in 10 different positions. The examined optical setup relies on optical correlation based on developing optical Vanderlugt filters and its basics are described in this article. With the limitation of face database of 40 persons, the recognition is examined successfully with nearly 100% of accuracy in matching the input images with their respective Vanderlugt synthesized filters. Software simulation is implemented by using MATLAB for face identification.
基金supported in part by the National Basic Research Program of China(973 Program)under Grant 2013CB336600the Beijing Natural Science Foundation under Grant 4131003+1 种基金the National Natural Science Foundation of China under Grant{61201187,61422109}the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions under Grant YETP0110
文摘In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,etc.This new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power level.Compared to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization strategy.The key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis testing.We discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are presented.Numerical examples are provided to corroborate the proposed studies.
文摘Gender recognition has gained more attention. However, most of the studies have focused on face images acquired under controlled conditions. In this paper, we investigate gender recognition on real-life faces. We proposed a gender recognition scheme, which is composed of four parts: face detection, median filter, feature extraction, and gender classifier. MULBP features are adopted and combined with a SVM classifier for gender recognition. The MULBP feature is robust to noise and illumination variations. In the experiment, we obtain 98.32% using LFW database and 97.30% on Samsung Gender dataset, which shows the superior performance in gender recognition compared with the conventional operators.
