In this work, we propose an original approach of semi-vectorial hybrid morphological segmentation for multicomponent images or multidimensional data by analyzing compact multidimensional histograms based on different ...In this work, we propose an original approach of semi-vectorial hybrid morphological segmentation for multicomponent images or multidimensional data by analyzing compact multidimensional histograms based on different orders. Its principle consists first of segment marginally each component of the multicomponent image into different numbers of classes fixed at K. The segmentation of each component of the image uses a scalar segmentation strategy by histogram analysis;we mainly count the methods by searching for peaks or modes of the histogram and those based on a multi-thresholding of the histogram. It is the latter that we have used in this paper, it relies particularly on the multi-thresholding method of OTSU. Then, in the case where i) each component of the image admits exactly K classes, K vector thresholds are constructed by an optimal pairing of which each component of the vector thresholds are those resulting from the marginal segmentations. In addition, the multidimensional compact histogram of the multicomponent image is computed and the attribute tuples or ‘colors’ of the histogram are ordered relative to the threshold vectors to produce (K + 1) intervals in the partial order giving rise to a segmentation of the multidimensional histogram into K classes. The remaining colors of the histogram are assigned to the closest class relative to their center of gravity. ii) In the contrary case, a vectorial spatial matching between the classes of the scalar components of the image is produced to obtain an over-segmentation, then an interclass fusion is performed to obtain a maximum of K classes. Indeed, the relevance of our segmentation method has been highlighted in relation to other methods, such as K-means, using unsupervised and supervised quantitative segmentation evaluation criteria. So the robustness of our method relatively to noise has been tested.展开更多
A multi-proxy quantum group signature scheme with threshold shared verification is proposed. An original signer may authorize a proxy group as his proxy agent. Then only the cooperation of all the signers in the proxy...A multi-proxy quantum group signature scheme with threshold shared verification is proposed. An original signer may authorize a proxy group as his proxy agent. Then only the cooperation of all the signers in the proxy group can generate the proxy signature on behalf of the original signer. In the scheme, any t or more of n receivers can verify the message and any t - 1 or fewer receivers cannot verify the validity of the proxy signature.展开更多
To address the problem that existing bipartite secret sharing scheme is short of dynamic characteristic, and to solve the problem that each participant can only use secret share once, this paper proposed a bipartite (...To address the problem that existing bipartite secret sharing scheme is short of dynamic characteristic, and to solve the problem that each participant can only use secret share once, this paper proposed a bipartite (n1+n2, m1+m2)-threshold multi-secret sharing scheme which combined cryptography and hypersphere geometry. In this scheme, we introduced a bivariate function and a coordinate function over finite field Zp to calculate the derived points of secret share, which can reconstruct the shared secrets by producing the intersection point of hypernormal plane and normal line on the hypertangent plane. At the initial stage the secret dealer distributes to each participant a secret share that can be kept secret based on the intractability of discrete logarithm problem and need not be changed with updating the shared secrets.Each cooperative participant only needs to submit a derived point calculated from the secret share without exposing this secret share during the process of reconstructing the shared secret. Analyses indicate that the proposed scheme is not only sound and secure because of hypersphere geometric properties and the difficulty of discrete logarithm problem, but also efficient because of its well dynamic behavior and the invariant secret share. Therefore, this bipartite threshold multi-secret sharing scheme is easy to implement and is applicable in practical settings.展开更多
A multi-hole vertical-cavity surface-emitting laser （VCSEL） operating in stable single mode with a low threshold current was produced by introducing multi-leaf scallop holes on the top distributed Bragg-refleetor of...A multi-hole vertical-cavity surface-emitting laser （VCSEL） operating in stable single mode with a low threshold current was produced by introducing multi-leaf scallop holes on the top distributed Bragg-refleetor of an oxidation- confined 850 nm VCSEL. The single-mode output power of 2.6 mW, threshold current of 0.6 mA, full width of half maximum lasing spectrum of less than 0.1 nm, side mode suppression ratio of 28.4 dB, and far-field divergence angle of about 10% are obtained. The effects of different hole depths on the optical characteristics are simulated and analysed, including far-field divergence, spectrum and lateral cavity mode. The single-mode performance of this multi-hole device is attributed to the large radiation loss from the inter hole spacing and the scattering loss at the bottom of the holes, particularly for higher order modes.展开更多
Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and...Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon measures such as Havrda & Charvat’s entropy, which is commonly used in gray level image analysis in many types of images such as satellite grayscale images. The proposed edge detection performance is compared to the previous classic methods, such as Roberts, Prewitt, and Sobel methods. Numerical results underline the robustness of the presented approach and different applications are shown.展开更多
The requirement for guaranteed Quality of Service (QoS) have become very essential since there are numerous network base application is available such as video conferencing, data streaming, data transfer and many more...The requirement for guaranteed Quality of Service (QoS) have become very essential since there are numerous network base application is available such as video conferencing, data streaming, data transfer and many more. This has led to the multi-class switch architecture to cater for the needs for different QoS requirements. The introduction of threshold in multi-class switch to solve the starvation problems in loss sensitive class has increased the mean delay for delay sensitive class. In this research, a new scheduling architecture is introduced to improve mean delay in delay sensitive class when the threshold is active. The proposed architecture has been simulated under uniform and non-uniform traffic to show performance of the switch in terms of mean delay. The results show that the proposed architecture has achieved better performance as compared to Weighted Fair Queueing (WFQ) and Priority Queue (PQ).展开更多
多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用...多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用与后悔机制的多尺度混合模型,克服了传统模型未考虑路径熟悉度导致的乘客出行行为与实际出行行为之间的决策偏差.通过整合容忍阈值与决策惯性,提出一种多交路出行选择建模方法,基于典型案例的陈述偏好(stated preference,SP)调查数据,完成模型参数估计与性能验证.研究结果表明,乘客对出行时间属性的容忍阈值为6.98 min;相较于基准模型,考虑决策惯性的模型在似然值、贝叶斯信息准则(Bayesian information criterion,BIC)及命中率指标上均表现更优,表明其具备更强的数据拟合能力;支付意愿分析进一步揭示乘客愿意为服务提升承担额外时间成本,从而验证了所提模型的有效性与实用性.展开更多
该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对...该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对于驾驶员面部疲劳状态检测及提醒的准确性和良好的系统性能。EAR、MAR、HPE 3种判断准则在公开数据集Drowsiness、YawDD及自制数据集上分别达到95.6%、96%与96%的平均正确率;在面部无遮挡的情况下,该系统实时帧率达到20 FPS,基本可实时对驾驶员疲劳状态作出相应提醒,同时具备较高的准确率。展开更多
驾驶员在实际驾驶的过程中会存在面部遮挡场景,例如戴眼镜、戴口罩等,传统单一通过提取驾驶员面部特征进行疲劳检测的Dlib算法不再适用。该文结合Dlib与YOLO11使用多阈值判定,对传统Dlib疲劳检测算法进行改进,给出戴眼镜、戴口罩等驾驶...驾驶员在实际驾驶的过程中会存在面部遮挡场景,例如戴眼镜、戴口罩等,传统单一通过提取驾驶员面部特征进行疲劳检测的Dlib算法不再适用。该文结合Dlib与YOLO11使用多阈值判定,对传统Dlib疲劳检测算法进行改进,给出戴眼镜、戴口罩等驾驶员面部遮挡场景的疲劳检测算法,并在Raspberry Pi 5硬件平台,使用公开数据集验证改进算法对于驾驶员疲劳检测的准确性。另外,改进算法还可以对吸烟、打电话等这类分心驾驶行为进行检测和语音提醒,对疲劳和分心行为实现更全面的检测和预警。展开更多
文摘In this work, we propose an original approach of semi-vectorial hybrid morphological segmentation for multicomponent images or multidimensional data by analyzing compact multidimensional histograms based on different orders. Its principle consists first of segment marginally each component of the multicomponent image into different numbers of classes fixed at K. The segmentation of each component of the image uses a scalar segmentation strategy by histogram analysis;we mainly count the methods by searching for peaks or modes of the histogram and those based on a multi-thresholding of the histogram. It is the latter that we have used in this paper, it relies particularly on the multi-thresholding method of OTSU. Then, in the case where i) each component of the image admits exactly K classes, K vector thresholds are constructed by an optimal pairing of which each component of the vector thresholds are those resulting from the marginal segmentations. In addition, the multidimensional compact histogram of the multicomponent image is computed and the attribute tuples or ‘colors’ of the histogram are ordered relative to the threshold vectors to produce (K + 1) intervals in the partial order giving rise to a segmentation of the multidimensional histogram into K classes. The remaining colors of the histogram are assigned to the closest class relative to their center of gravity. ii) In the contrary case, a vectorial spatial matching between the classes of the scalar components of the image is produced to obtain an over-segmentation, then an interclass fusion is performed to obtain a maximum of K classes. Indeed, the relevance of our segmentation method has been highlighted in relation to other methods, such as K-means, using unsupervised and supervised quantitative segmentation evaluation criteria. So the robustness of our method relatively to noise has been tested.
基金Project supported by the National Basic Research Program of China (973 Program) (Grant No 2007CB311100)the National High Technology Research and Development Program of China (Grant Nos 2006AA01Z419 and 20060101Z4015)+4 种基金the Major Research plan of the National Natural Science Foundation of China (Grant No 90604023)2008 Scientific Research Common Program of Beijing Municipal Commission of Education The Scientific Research Foundation for the Youth of Beijing University of Technology (Grant No 97007016200701)the National Research Foundation for the Doctoral Program of Higher Educationof China (Grant No 20040013007)the National Laboratory for Modern Communications Science Foundation of China (GrantNo 9140C1101010601)the Doctor Scientific Research Activation Foundation of Beijing University of Technology (Grant No 52007016200702)
文摘A multi-proxy quantum group signature scheme with threshold shared verification is proposed. An original signer may authorize a proxy group as his proxy agent. Then only the cooperation of all the signers in the proxy group can generate the proxy signature on behalf of the original signer. In the scheme, any t or more of n receivers can verify the message and any t - 1 or fewer receivers cannot verify the validity of the proxy signature.
文摘To address the problem that existing bipartite secret sharing scheme is short of dynamic characteristic, and to solve the problem that each participant can only use secret share once, this paper proposed a bipartite (n1+n2, m1+m2)-threshold multi-secret sharing scheme which combined cryptography and hypersphere geometry. In this scheme, we introduced a bivariate function and a coordinate function over finite field Zp to calculate the derived points of secret share, which can reconstruct the shared secrets by producing the intersection point of hypernormal plane and normal line on the hypertangent plane. At the initial stage the secret dealer distributes to each participant a secret share that can be kept secret based on the intractability of discrete logarithm problem and need not be changed with updating the shared secrets.Each cooperative participant only needs to submit a derived point calculated from the secret share without exposing this secret share during the process of reconstructing the shared secret. Analyses indicate that the proposed scheme is not only sound and secure because of hypersphere geometric properties and the difficulty of discrete logarithm problem, but also efficient because of its well dynamic behavior and the invariant secret share. Therefore, this bipartite threshold multi-secret sharing scheme is easy to implement and is applicable in practical settings.
基金Project supported by the National High Technology Research and Development Program of China (Grant No. 2008AA03Z402)the National Natural Science Foundation of China (Grant No. 61076044)the Natural Science Foundation of Beijing,China(Grant Nos. 4092007 and 4102003)
文摘A multi-hole vertical-cavity surface-emitting laser （VCSEL） operating in stable single mode with a low threshold current was produced by introducing multi-leaf scallop holes on the top distributed Bragg-refleetor of an oxidation- confined 850 nm VCSEL. The single-mode output power of 2.6 mW, threshold current of 0.6 mA, full width of half maximum lasing spectrum of less than 0.1 nm, side mode suppression ratio of 28.4 dB, and far-field divergence angle of about 10% are obtained. The effects of different hole depths on the optical characteristics are simulated and analysed, including far-field divergence, spectrum and lateral cavity mode. The single-mode performance of this multi-hole device is attributed to the large radiation loss from the inter hole spacing and the scattering loss at the bottom of the holes, particularly for higher order modes.
文摘Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon measures such as Havrda & Charvat’s entropy, which is commonly used in gray level image analysis in many types of images such as satellite grayscale images. The proposed edge detection performance is compared to the previous classic methods, such as Roberts, Prewitt, and Sobel methods. Numerical results underline the robustness of the presented approach and different applications are shown.
文摘The requirement for guaranteed Quality of Service (QoS) have become very essential since there are numerous network base application is available such as video conferencing, data streaming, data transfer and many more. This has led to the multi-class switch architecture to cater for the needs for different QoS requirements. The introduction of threshold in multi-class switch to solve the starvation problems in loss sensitive class has increased the mean delay for delay sensitive class. In this research, a new scheduling architecture is introduced to improve mean delay in delay sensitive class when the threshold is active. The proposed architecture has been simulated under uniform and non-uniform traffic to show performance of the switch in terms of mean delay. The results show that the proposed architecture has achieved better performance as compared to Weighted Fair Queueing (WFQ) and Priority Queue (PQ).
文摘多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用与后悔机制的多尺度混合模型,克服了传统模型未考虑路径熟悉度导致的乘客出行行为与实际出行行为之间的决策偏差.通过整合容忍阈值与决策惯性,提出一种多交路出行选择建模方法,基于典型案例的陈述偏好(stated preference,SP)调查数据,完成模型参数估计与性能验证.研究结果表明,乘客对出行时间属性的容忍阈值为6.98 min;相较于基准模型,考虑决策惯性的模型在似然值、贝叶斯信息准则(Bayesian information criterion,BIC)及命中率指标上均表现更优,表明其具备更强的数据拟合能力;支付意愿分析进一步揭示乘客愿意为服务提升承担额外时间成本,从而验证了所提模型的有效性与实用性.
文摘该文运用Dlib人脸检测模型与人脸检测模板匹配方法,通过计算EAR、MAR、pitch、yaw和roll参数,采用多阈值判定研究疲驾驶员疲劳状态,并将该算法在Raspberry Pi 5硬件平台实现,搭建疲劳驾驶检测预警系统,最后通过公开数据集验证该系统对于驾驶员面部疲劳状态检测及提醒的准确性和良好的系统性能。EAR、MAR、HPE 3种判断准则在公开数据集Drowsiness、YawDD及自制数据集上分别达到95.6%、96%与96%的平均正确率;在面部无遮挡的情况下,该系统实时帧率达到20 FPS,基本可实时对驾驶员疲劳状态作出相应提醒,同时具备较高的准确率。
文摘驾驶员在实际驾驶的过程中会存在面部遮挡场景,例如戴眼镜、戴口罩等,传统单一通过提取驾驶员面部特征进行疲劳检测的Dlib算法不再适用。该文结合Dlib与YOLO11使用多阈值判定,对传统Dlib疲劳检测算法进行改进,给出戴眼镜、戴口罩等驾驶员面部遮挡场景的疲劳检测算法,并在Raspberry Pi 5硬件平台,使用公开数据集验证改进算法对于驾驶员疲劳检测的准确性。另外,改进算法还可以对吸烟、打电话等这类分心驾驶行为进行检测和语音提醒,对疲劳和分心行为实现更全面的检测和预警。
