The essential tool in image processing,computer vision and machine vision is edge detection,especially in the fields of feature extraction and feature detection.Entropy is a basic area in information theory.The entrop...The essential tool in image processing,computer vision and machine vision is edge detection,especially in the fields of feature extraction and feature detection.Entropy is a basic area in information theory.The entropy,in image processing field has a role associated with image settings.As an initial step in image processing,the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in image.Image segmentation known as the process which divides the image into multiple regions or sets of pixels.Many applications have been development to enhance the image processing.This paper utilizes the Shannon entropy to achieve edge detection process and segmentation of the image.It introduces a new method of edge detection for 2-D histogram and Shannon entropy based on multilevel threshold.The method utilizes the gray value and the average gray value of the pixels to achieve the two dimensional histogram.The current method has apriority in comparison to some upper classical methods.The experimental results exhibited that the proposed method could capture a moderate quality and execution time better than other comparative methods,particularly in the largest images size.The proposed method offers good results when applied with images of different sizes from the civilization of ancient Egyptians.展开更多
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class unifo...Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.展开更多
A new method for fabricating ordered porous silicon is reported. A two-dimensional silica nanosphere array is used as a template with a hydrofluoric acid-hydrogen peroxide solution for etching the nanospheres. The ini...A new method for fabricating ordered porous silicon is reported. A two-dimensional silica nanosphere array is used as a template with a hydrofluoric acid-hydrogen peroxide solution for etching the nanospheres. The initial diameter and distribution of the holes in the resulting porous silicon layer are determined by the size and distribution of the silica nanospheres. The corrosion time can be used to control the depths of the holes. It is found that the presence of a SiO2 layer, formed by the oxidation of the rough internal surface of the hole, is the primary reason allowing the corrosion to proceed. Ultraviolet reflection and thermal conductivity measurements show that the diameter and distribution of the holes have a great influence on properties of the porous silicon.展开更多
At thermal ultra-cold neutron (UCN) sources (neutrons in thermal equilibrium with the moderator) only a very small fraction of neutrons have velocities ~6 m/s. Therefore, the UCN production rate cannot be substantiall...At thermal ultra-cold neutron (UCN) sources (neutrons in thermal equilibrium with the moderator) only a very small fraction of neutrons have velocities ~6 m/s. Therefore, the UCN production rate cannot be substantially increased by simply lowering the temperature of the moderator. The new approach is to use the super-thermal principle, i.e., neutrons not in thermal equilibrium with the converter. We want to investigate scattering kernels for a super-thermal UCN source based on a two-layer arrangement of D2O and solid D2. The solid D2 (sD2) at temperature 8 K is kept in close contact with D2O moderator at room temperature. Using the MCNP code, the fast neutron flux on the spallation target, the thermal flux in the D2O near the sD2, and the cold flux in the sD2 are simulated. For a given cold flux, neutron transport equations are calculated. In order to obtain precise neutron scattering kernels, and consequently UCN flux and density, 330 neutron energy groups have been taken. The coupled energy dependent transport equations have been solved by combining MCNPX code with an analytical approach and using implicit method in MATLAB. We have obtained an optimal dimension for the UCN source. A suitable space step has been taken for the numerical stability.展开更多
文摘The essential tool in image processing,computer vision and machine vision is edge detection,especially in the fields of feature extraction and feature detection.Entropy is a basic area in information theory.The entropy,in image processing field has a role associated with image settings.As an initial step in image processing,the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in image.Image segmentation known as the process which divides the image into multiple regions or sets of pixels.Many applications have been development to enhance the image processing.This paper utilizes the Shannon entropy to achieve edge detection process and segmentation of the image.It introduces a new method of edge detection for 2-D histogram and Shannon entropy based on multilevel threshold.The method utilizes the gray value and the average gray value of the pixels to achieve the two dimensional histogram.The current method has apriority in comparison to some upper classical methods.The experimental results exhibited that the proposed method could capture a moderate quality and execution time better than other comparative methods,particularly in the largest images size.The proposed method offers good results when applied with images of different sizes from the civilization of ancient Egyptians.
基金Supported by the CRSRI Open Research Program(CKWV2013225/KY)the Priority Academic Program Development of Jiangsu Higher Education Institution+2 种基金the Open Project Foundation of Key Laboratory of the Yellow River Sediment of Ministry of Water Resource(2014006)the State Key Lab of Urban Water Resource and Environment(HIT)(ES201409)the Open Project Program of State Key Laboratory of Food Science and Technology,Jiangnan University(SKLF-KF-201310)
文摘Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
基金Supported by the National Natural Science Foundation of China under Grant Nos 10804026 and 51101049the Natural Science Foundation of Hebei Province under Grant Nos A2013205101 and A2014205051the Hebei Talent Cultivation Foundation under Grant No A201400119
文摘A new method for fabricating ordered porous silicon is reported. A two-dimensional silica nanosphere array is used as a template with a hydrofluoric acid-hydrogen peroxide solution for etching the nanospheres. The initial diameter and distribution of the holes in the resulting porous silicon layer are determined by the size and distribution of the silica nanospheres. The corrosion time can be used to control the depths of the holes. It is found that the presence of a SiO2 layer, formed by the oxidation of the rough internal surface of the hole, is the primary reason allowing the corrosion to proceed. Ultraviolet reflection and thermal conductivity measurements show that the diameter and distribution of the holes have a great influence on properties of the porous silicon.
文摘At thermal ultra-cold neutron (UCN) sources (neutrons in thermal equilibrium with the moderator) only a very small fraction of neutrons have velocities ~6 m/s. Therefore, the UCN production rate cannot be substantially increased by simply lowering the temperature of the moderator. The new approach is to use the super-thermal principle, i.e., neutrons not in thermal equilibrium with the converter. We want to investigate scattering kernels for a super-thermal UCN source based on a two-layer arrangement of D2O and solid D2. The solid D2 (sD2) at temperature 8 K is kept in close contact with D2O moderator at room temperature. Using the MCNP code, the fast neutron flux on the spallation target, the thermal flux in the D2O near the sD2, and the cold flux in the sD2 are simulated. For a given cold flux, neutron transport equations are calculated. In order to obtain precise neutron scattering kernels, and consequently UCN flux and density, 330 neutron energy groups have been taken. The coupled energy dependent transport equations have been solved by combining MCNPX code with an analytical approach and using implicit method in MATLAB. We have obtained an optimal dimension for the UCN source. A suitable space step has been taken for the numerical stability.
