An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluat...An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluation functions,the variance function and the Brenner function are synthesized as a new evaluation function.In the first step,a self-adaptive step length which is much dependent on the reciprocal of the evaluation function value at the beginning position of climbing is used for approaching the halfway up the mountain roughly.Secondly,a fixed moderate step length is applied for approaching the mountaintop of the variance function as closer as possible.Finally,afine step is employed for reaching the exact mountaintop of the Brenner function.The microscope auto-focusing experiments based on the proposed algorithm for blood smear detection have been carried out comprehensively.The results show that the improved algorithm can not only guarantee the precision to get clear focal images,but also improve the auto-focusing e±ciency.展开更多
A real-time auto-focusing system with auto-collimation method is introduced, which is used in auto-detecting the focus of the space camera with long focus. Auto-focusing is the key technique to ensure high quality in ...A real-time auto-focusing system with auto-collimation method is introduced, which is used in auto-detecting the focus of the space camera with long focus. Auto-focusing is the key technique to ensure high quality in space imaging. It can measure and compensate the defocus caused by the change of temperature and air pressure etc. in space. To solve the problem of auto-focusing with auto-collimation method of the camera whose axis is perpendicular to the ground, it is designed that two small caliber pentagonal prisms are placed in the area of aperture suitable to the camera’s relative aperture based on the theory of auto-focusing with auto-collimation, which can replace the big caliber plane reflector used in other cameras. Using the characteristic of pentagonal prism refracting light vertically, the target slit is imaged in CCD through the two-separated lens. It transforms the detecting of the axial defocusing quantity to the landscape orientation measurement of the faculae’s position in the direction of CCD pixels. The defocusing quantity is obtained by measuring the opposite position of the two faculae on the CCD. The Centroid method is adopted to measure the position of the auto-collimation faculae. The arithmetic error is analyzed especially, and the causation is given. Experiments show that this real-time auto-focusing system using centroid method is reliable and the focusing precision can reach ±0.01 mm.展开更多
When interference microscope measures the surface rough of the micromechanical device, as soon as the work distance of interference microscope and the depth of field is shortened, the interference images become slur f...When interference microscope measures the surface rough of the micromechanical device, as soon as the work distance of interference microscope and the depth of field is shortened, the interference images become slur for the measured object if there has small interference after clear focus. The auto-focusing system is introduced into the interference microscope, the system can obtain high definition interference image rapidly,and can improve the measuring velocity and measuring precision. The system is characterized by auto-focusing range of ±150 μm, auto-focusing precision of ±0.3 μm, auto-focusing time of 4～8 s.展开更多
This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image ...This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image sensor, and a driver IC of the motor. The sizes of the AF (auto-focus) module are 8.5 mm×8.5 mm×5.9 mm. The piezoelectric elements are bonded on the external surface of the stator. The rotor has external screw thread that engages with the inner screw thread of the stator. When the piezoelectric elements are excited by the driver IC, a bend traveling wave in plane is generated on the stator along the circle direction, that drives the lens rotor to rotate and then to move axially. The driver IC is controlled by an image feedback of an image sensor centered on the axis of the casing, then the optical focusing is realized. The power consumption is zero at rest and is less than 0.25 W in motion; focusing precision <10 μm; speed >3 r/s(180 r/min); response <10 ms; high reliability: resistant to shock and fall off; directly driven by the driver IC without transmission mechanism; the friction force is namely the driving force and noiseless. The integrated optical auto-focus system is very useful, especially for cellular phones. The image resolution of 3―5 MP has been obtained in the module prototypes of the cellular phone.展开更多
Auto-focus is very important for capturing sharp human face centered images in digital and smart phone cameras. With the development of image sensor technology, these cameras support more and more highresolution image...Auto-focus is very important for capturing sharp human face centered images in digital and smart phone cameras. With the development of image sensor technology, these cameras support more and more highresolution images to be processed. Currently it is difficult to support fast auto-focus at low power consumption on high-resolution images. This work proposes an efficient architecture for an Ada Boost-based face-priority auto-focus. The architecture supports block-based integral image computation to improve the processing speed on high-resolution images; meanwhile, it is reconfigurable so that it enables the sub-window adaptive cascade classification, which greatly improves the processing speed and reduces power consumption. Experimental results show that 96% detection rate in average and 58 fps(frame per second) detection speed are achieved for the1080p(1920×1080) images. Compared with the state-of-the-art work, the detection speed is greatly improved and power consumption is largely reduced.展开更多
探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成...探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成像算法需要预知背景介质的相对介电常数,且需逐个计算各成像网格的散射强度值,计算效率低.本文提出一种基于深度学习的探地雷达自聚焦后向投影(Deep learning based Auto focusing BP,DABP)成像方法,设计了目标感兴趣区域(Region Of Interest,ROI)的检测模块,基于地下目标的空间稀疏特征,将YOLOX网络和BP成像机理相结合,快速检测出目标潜在区域,仅对该区域中的成像网格进行成像处理,避免全域的后向投影计算,大幅降低运算量.其次,针对介电常数未知情况下BP成像难以聚焦的问题,设计了一个自聚焦后向投影(Auto Focusing BP,AF-BP)成像模块,构建了BS-YOLOv5网络和相应的数据集,实现基于改进二分法的地下介质介电常数估计和自聚焦成像.然后,设计了一个基于双阈值和积分聚焦的伪影抑制(artifact suppression based on Double Threshold and Integral Focusing,DTIF)模块,进一步提高成像结果的聚焦度.开展了仿真和实测数据的成像处理和对比分析,与BP成像方法相比,仿真数据成像结果的ISLR指标下降了250%、SCR指标提升了131%;实测数据成像结果的ISLR指标下降了322%、SCR指标提升了72%,仿真实验和实测实验的成像速度均提升了300%,验证了所提方法在提高GPR成像效率和成像质量方面的有效性.展开更多
The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem ...The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.展开更多
基金This work is supported by 863 National Plan Foundation of China under grant No.2007 AA01Z333.
文摘An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluation functions,the variance function and the Brenner function are synthesized as a new evaluation function.In the first step,a self-adaptive step length which is much dependent on the reciprocal of the evaluation function value at the beginning position of climbing is used for approaching the halfway up the mountain roughly.Secondly,a fixed moderate step length is applied for approaching the mountaintop of the variance function as closer as possible.Finally,afine step is employed for reaching the exact mountaintop of the Brenner function.The microscope auto-focusing experiments based on the proposed algorithm for blood smear detection have been carried out comprehensively.The results show that the improved algorithm can not only guarantee the precision to get clear focal images,but also improve the auto-focusing e±ciency.
文摘A real-time auto-focusing system with auto-collimation method is introduced, which is used in auto-detecting the focus of the space camera with long focus. Auto-focusing is the key technique to ensure high quality in space imaging. It can measure and compensate the defocus caused by the change of temperature and air pressure etc. in space. To solve the problem of auto-focusing with auto-collimation method of the camera whose axis is perpendicular to the ground, it is designed that two small caliber pentagonal prisms are placed in the area of aperture suitable to the camera’s relative aperture based on the theory of auto-focusing with auto-collimation, which can replace the big caliber plane reflector used in other cameras. Using the characteristic of pentagonal prism refracting light vertically, the target slit is imaged in CCD through the two-separated lens. It transforms the detecting of the axial defocusing quantity to the landscape orientation measurement of the faculae’s position in the direction of CCD pixels. The defocusing quantity is obtained by measuring the opposite position of the two faculae on the CCD. The Centroid method is adopted to measure the position of the auto-collimation faculae. The arithmetic error is analyzed especially, and the causation is given. Experiments show that this real-time auto-focusing system using centroid method is reliable and the focusing precision can reach ±0.01 mm.
文摘When interference microscope measures the surface rough of the micromechanical device, as soon as the work distance of interference microscope and the depth of field is shortened, the interference images become slur for the measured object if there has small interference after clear focus. The auto-focusing system is introduced into the interference microscope, the system can obtain high definition interference image rapidly,and can improve the measuring velocity and measuring precision. The system is characterized by auto-focusing range of ±150 μm, auto-focusing precision of ±0.3 μm, auto-focusing time of 4～8 s.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 50577035, 10676015)High Technology Research and Development Program of China (863 Program) (Grant No. 2006AA02Z472)
文摘This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image sensor, and a driver IC of the motor. The sizes of the AF (auto-focus) module are 8.5 mm×8.5 mm×5.9 mm. The piezoelectric elements are bonded on the external surface of the stator. The rotor has external screw thread that engages with the inner screw thread of the stator. When the piezoelectric elements are excited by the driver IC, a bend traveling wave in plane is generated on the stator along the circle direction, that drives the lens rotor to rotate and then to move axially. The driver IC is controlled by an image feedback of an image sensor centered on the axis of the casing, then the optical focusing is realized. The power consumption is zero at rest and is less than 0.25 W in motion; focusing precision <10 μm; speed >3 r/s(180 r/min); response <10 ms; high reliability: resistant to shock and fall off; directly driven by the driver IC without transmission mechanism; the friction force is namely the driving force and noiseless. The integrated optical auto-focus system is very useful, especially for cellular phones. The image resolution of 3―5 MP has been obtained in the module prototypes of the cellular phone.
基金supported in part by China Major Science and Technology (S&T) Project (Grant No. 2013ZX01033-001-001-003)National High-Tech R&D Program of China (863) (Grant Nos. 2012AA012701, 2012AA0109-04)+2 种基金National Natural Science Foundation of China (Grant No. 61274131)International S&T Cooperation Project of China (Grant No. 2012DFA11170)Importation and Development of the High-Caliber Talents Project of Beijing Municipal Institutions (Grant No. YETP0163)
文摘Auto-focus is very important for capturing sharp human face centered images in digital and smart phone cameras. With the development of image sensor technology, these cameras support more and more highresolution images to be processed. Currently it is difficult to support fast auto-focus at low power consumption on high-resolution images. This work proposes an efficient architecture for an Ada Boost-based face-priority auto-focus. The architecture supports block-based integral image computation to improve the processing speed on high-resolution images; meanwhile, it is reconfigurable so that it enables the sub-window adaptive cascade classification, which greatly improves the processing speed and reduces power consumption. Experimental results show that 96% detection rate in average and 58 fps(frame per second) detection speed are achieved for the1080p(1920×1080) images. Compared with the state-of-the-art work, the detection speed is greatly improved and power consumption is largely reduced.
文摘探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成像算法需要预知背景介质的相对介电常数,且需逐个计算各成像网格的散射强度值,计算效率低.本文提出一种基于深度学习的探地雷达自聚焦后向投影(Deep learning based Auto focusing BP,DABP)成像方法,设计了目标感兴趣区域(Region Of Interest,ROI)的检测模块,基于地下目标的空间稀疏特征,将YOLOX网络和BP成像机理相结合,快速检测出目标潜在区域,仅对该区域中的成像网格进行成像处理,避免全域的后向投影计算,大幅降低运算量.其次,针对介电常数未知情况下BP成像难以聚焦的问题,设计了一个自聚焦后向投影(Auto Focusing BP,AF-BP)成像模块,构建了BS-YOLOv5网络和相应的数据集,实现基于改进二分法的地下介质介电常数估计和自聚焦成像.然后,设计了一个基于双阈值和积分聚焦的伪影抑制(artifact suppression based on Double Threshold and Integral Focusing,DTIF)模块,进一步提高成像结果的聚焦度.开展了仿真和实测数据的成像处理和对比分析,与BP成像方法相比,仿真数据成像结果的ISLR指标下降了250%、SCR指标提升了131%;实测数据成像结果的ISLR指标下降了322%、SCR指标提升了72%,仿真实验和实测实验的成像速度均提升了300%,验证了所提方法在提高GPR成像效率和成像质量方面的有效性.
基金The Natural Science Foundation of Jiangsu Province(NoBK2008429)Open Research Foundation of State Key Laboratory ofMillimeter Waves of Southeast University(NoK200903)+1 种基金China Postdoctoral Science Foundation(No20080431126)Jiangsu Province Postdoctoral Science Foundation(No2007337)
文摘The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.
