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1.发明授权Raman spectroscopy method of measuring melamine contents in dairy products having different matrixes 有权测量具有不同基质的乳制品中三聚氰胺含量的拉曼光谱法公开(公告)号：US08891081B1
公开(公告)日：2014-11-18
申请号：US14145454
申请日：2013-12-31
发明人： Zhiqiang Chen , Li Zhang , Jianhong Zhang , Hongqui Wang , Ziran Zhao , Jianping Gu , Zhiming Wang , Qingping Huang , Yumin Yi
CPC分类号： G01N21/65
摘要： A raman spectroscopy method of measuring melamine contents in dairy products having different matrixes. The method includes: (a) establishing a database of characteristic curves of dairy products having different matrixes; (b) taking several copies of the dairy products having one certain unknown matrix and adding melamine standard solutions having different concentrations therein, to obtain a series of dairy product samples in which the relative concentrations of the melamine are known; (c) performing raman spectrum testing analysis and obtaining corresponding characteristic peak intensities to obtain a slope of the characteristic curve showing variation of the characteristic peak intensities with the relative concentrations of the melamine; (d) searching the database of step (a) using the slope of the characteristic curve of the dairy product samples to find a matching characteristic curve, and (e) calculating concentration of melamine in the dairy products by using the matched characteristic curve and the characteristic peak intensity.
摘要翻译： 测量具有不同基质的乳制品中三聚氰胺含量的拉曼光谱法。 该方法包括：（a）建立具有不同矩阵的乳制品特征曲线数据库; （b）取几份具有一定未知基质的乳制品，并加入其中浓度不同的三聚氰胺标准溶液，以获得其中已知三聚氰胺的相对浓度的一系列乳制品样品; （c）进行拉曼光谱测试分析并获得相应的特征峰强度，以获得特征曲线的斜率，显示特征峰强度与三聚氰胺的相对浓度的变化; （d）使用乳制品样品的特征曲线的斜率来搜索步骤（a）的数据库，以找到匹配的特征曲线，以及（e）通过使用匹配的特征曲线计算乳制品中三聚氰胺的浓度， 特征峰强度。
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公开(公告)号：US10152774B2
公开(公告)日：2018-12-11
申请号：US15217613
申请日：2016-07-22
发明人： Kejun Kang , Zhiqiang Chen , Yuanjing Li , Li Zhang , Ziran Zhao , Yaohong Liu , Jianping Gu , Zhiming Wang
摘要： The present disclosure relates to a method and device for estimating a point spread function. In one implementation, a method includes capturing, by a scanning device, an image by scanning a plurality of rectangle blocks which are same sized and closely arranged, wherein the plurality of rectangle blocks are made of different materials and/or have different mass thicknesses, and an incident direction of rays is perpendicular to a scanning direction and a surface of the plurality of rectangle blocks arranged closely during scanning; obtaining line spread functions for two directions along a length side and a width side of each of the rectangle blocks based on the scanned image, and obtaining standard deviation parameters of the line spread functions; and combining the standard deviation parameters for the two directions to obtain a two dimensional Point Spread Function (PSF) parameter so as to estimate the point spread function.
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公开(公告)号：US20180040115A1
公开(公告)日：2018-02-08
申请号：US15610930
申请日：2017-06-01
发明人： Zhiqiang Chen , Yuanjing Li , Ziran Zhao , Yaohong Liu , Jianping Gu , Zhiming Wang
IPC分类号： G06T7/00
CPC分类号： G06T7/0002 , G06T2207/20016 , G06T2207/20064 , G06T2207/30168
摘要： A method and an apparatus for estimating an image fuzziness are provided. The method may comprise: acquiring an image; obtaining a mufti-scale representation of the image by performing a mufti-scale transform on the image; calculating gradients of the image and a normalized histogram of the gradients at each scale based on the multi-scale representation; calculating error vectors between the normalized histogram of gradients at each scale and a normalized original histogram of gradients of the image; performing a weighted summing on the error vectors by using respective weights to obtain a summed result, wherein the weights are determined based on a reciprocal of the sums of squares of the gradients of the image at each scale; estimating the ambiguity of the image based on the summed result.
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公开(公告)号：US10332244B2
公开(公告)日：2019-06-25
申请号：US15610930
申请日：2017-06-01
发明人： Zhiqiang Chen , Yuanjing Li , Ziran Zhao , Yaohong Liu , Jianping Gu , Zhiming Wang
IPC分类号： G06T7/00
摘要： A method and an apparatus for estimating an image fuzziness are provided. The method may comprise: acquiring an image; obtaining a multi-scale representation of the image by performing a multi-scale transform on the image; calculating gradients of the image and a normalized histogram of the gradients at each scale based on the multi-scale representation; calculating error vectors between the normalized histogram of gradients at each scale and a normalized original histogram of gradients of the image; performing a weighted summing on the error vectors by using respective weights to obtain a summed result, wherein the weights are determined based on a reciprocal of the sums of squares of the gradients of the image at each scale; estimating the ambiguity of the image based on the summed result.
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公开(公告)号：US10267678B2
公开(公告)日：2019-04-23
申请号：US14577748
申请日：2014-12-19
发明人： Ziran Zhao , Jianhong Zhang , Hongqiu Wang , Weiwei Wang , Zhiming Wang , Yumin Yi
摘要： Embodiments of the present invention provide a Raman spectroscopic inspection method, comprising the steps of: measuring a Raman spectrum of an object to be inspected successively to collect a plurality of Raman spectroscopic signals; superposing the plurality of Raman spectroscopic signals to form a superposition signal; filtering out a florescence interfering signal from the superposition signal; and identifying the object to be inspected on basis of the superposition signal from which the florescence interfering signal has been filtered out. By means of the above method, a desired Raman spectroscopic signal may be acquired by removing the interference caused by a florescence signal from a Raman spectroscopic inspection signal of the object. It may inspect correctly the characteristics of the Raman spectrum of the object so as to identify the object effectively.
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公开(公告)号：US10217204B2
公开(公告)日：2019-02-26
申请号：US15409738
申请日：2017-01-19
发明人： Zhiqiang Chen , Yuanjing Li , Li Zhang , Ziran Zhao , Yaohong Liu , Jianping Gu , Zhiming Wang
摘要： A method of evaluating an image quality for an imaging system and the imaging system are provided. The method in some examples includes: acquiring an image to be evaluated which is generated by the imaging system; extracting a number of sub-images from the image; obtaining a coefficient vector indicating a degree of sparsity by applying a sparse decomposition on the sub-images based on a pre-set redundant sparse representation dictionary; and performing a linear transformation on the coefficient vector so as to obtain an evaluation value for the image quality. The sparse dictionary is learned by only using a few high quality perspective images, and then the image quality is evaluated based on the sparse degree of the image obtained by using the sparse dictionary. A convenient and rapid no-reference image quality evaluation is achieved.
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