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1. 发明授权

US11361937B2 System and method for generating and analyzing roughness measurements and their use for process monitoring and control 有权
公开(公告)号：US11361937B2
公开(公告)日：2022-06-14
申请号：US17103185
申请日：2020-11-24
申请人： FRACTILIA, LLC
发明人： Chris Mack
IPC分类号： H01J37/22 , G06T7/13 , G06T7/40 , G06T7/42 , G06T7/49 , G06T5/00 , G01Q30/02 , G01Q30/06 , H01J37/28
摘要： A method is disclosed. The method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information, determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, and analyzing the feature edge positions to detect the presence or absence of defects in the pattern structure.

2. 发明申请

US20220130159A1 SYSTEM AND METHOD FOR DETECTING THE AUTHENTICITY OF PRODUCTS 有权
公开(公告)号：US20220130159A1
公开(公告)日：2022-04-28
申请号：US17647237
申请日：2022-01-06
申请人： Guy LE HENAFF
发明人： Guy LE HENAFF
IPC分类号： G06V20/80 , G06F16/583 , G06T5/40 , G06T7/44 , G06T5/00 , G06T7/42 , G06T7/70 , G06K9/00 , G06V10/25 , G06V10/22 , G06K9/62 , G06K19/06 , G06T7/00
摘要： System and method for detecting the authenticity of products by detecting a unique chaotic signature. Photos of the products are taken at the plant and stored in a database/server. The server processes the images to detect for each authentic product a unique authentic signature which is the result of a manufacturing process, a process of nature etc. To detect whether the product is genuine or not at the store, the user/buyer may take a picture of the product and send it to the server (e.g. using an app installed on a portable device or the like). Upon receipt of the photo, the server may process the receive image in search for a pre-detected and/or pre-stored chaotic signature associated with an authentic product. The server may return a response to the user indicating the result of the search. A feedback mechanism may be included to guide the user to take a picture at a specific location of the product where the chaotic signature may exist.

3. 发明申请

US20210327675A1 SYSTEM AND METHOD FOR GENERATING AND ANALYZING ROUGHNESS MEASUREMENTS 有权
公开(公告)号：US20210327675A1
公开(公告)日：2021-10-21
申请号：US17316154
申请日：2021-05-10
申请人： FRACTILIA, LLC
发明人： Chris Mack
IPC分类号： H01J37/22 , G06T7/13 , G06T7/40 , G06T7/42 , G06T7/49 , G06T5/00 , H01J37/28 , G01Q30/02 , G01Q30/06
摘要： In one embodiment, a method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, and identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information. The method also includes determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, analyzing the feature edge positions to determine errors in the manufacture of the pattern structure, and controlling a lithography tool based on the analysis of the feature edge positions.

4. 发明授权

US11004654B2 System and method for generating and analyzing roughness measurements 有权
公开(公告)号：US11004654B2
公开(公告)日：2021-05-11
申请号：US16730393
申请日：2019-12-30
申请人： FRACTILIA, LLC
发明人： Chris Mack
IPC分类号： H01J37/22 , G06T7/13 , G06T7/40 , G06T7/42 , G06T7/49 , G06T5/00 , H01J37/28 , G01Q30/02 , G01Q30/06
摘要： Systems and methods are disclosed that remove noise from roughness measurements to determine roughness of a feature in a pattern structure. In one embodiment, a method for determining roughness of a feature in a pattern structure includes generating, using an imaging device, a set of one or more images, each including measured linescan information that includes noise. The method also includes detecting edges of the features within the pattern structure of each image without filtering the images, generating a biased power spectral density (PSD) dataset representing feature geometry information corresponding to the edge detection measurements, evaluating a high-frequency portion of the biased PSD dataset to determine a noise model for predicting noise over all frequencies of the biased PSD dataset, and subtracting the noise predicted by the determined noise model from a biased roughness measure to obtain an unbiased roughness measure.

5. 发明申请

US20210082658A1 SYSTEM AND METHOD FOR GENERATING AND ANALYZING ROUGHNESS MEASUREMENTS AND THEIR USE FOR PROCESS MONITORING AND CONTROL 有权
公开(公告)号：US20210082658A1
公开(公告)日：2021-03-18
申请号：US17103185
申请日：2020-11-24
申请人： FRACTILIA, LLC
发明人： Chris Mack
IPC分类号： H01J37/22 , G06T7/13 , G06T7/40 , G06T7/42 , G06T7/49 , G06T5/00 , H01J37/28 , G01Q30/02 , G01Q30/06
摘要： A method is disclosed. The method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information, determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, and analyzing the feature edge positions to detect the presence or absence of defects in the pattern structure.

6. 发明申请

US20200211813A1 SYSTEM AND METHOD FOR GENERATING AND ANALYZING ROUGHNESS MEASUREMENTS 审中-公开
公开(公告)号：US20200211813A1
公开(公告)日：2020-07-02
申请号：US16730393
申请日：2019-12-30
申请人： FRACTILIA, LLC
发明人： Chris MACK
IPC分类号： H01J37/22 , G01Q30/06 , G01Q30/02 , H01J37/28 , G06T5/00 , G06T7/49 , G06T7/40 , G06T7/13 , G06T7/42
摘要： Systems and methods are disclosed that remove noise from roughness measurements to determine roughness of a feature in a pattern structure. In one embodiment, a method for determining roughness of a feature in a pattern structure includes generating, using an imaging device, a set of one or more images, each including measured linescan information that includes noise. The method also includes detecting edges of the features within the pattern structure of each image without filtering the images, generating a biased power spectral density (PSD) dataset representing feature geometry information corresponding to the edge detection measurements, evaluating a high-frequency portion of the biased PSD dataset to determine a noise model for predicting noise over all frequencies of the biased PSD dataset, and subtracting the noise predicted by the determined noise model from a biased roughness measure to obtain an unbiased roughness measure.

7. 发明授权

US10303986B2 Automated measurement of brain injury indices using brain CT images, injury data, and machine learning 有权
公开(公告)号：US10303986B2
公开(公告)日：2019-05-28
申请号：US13383351
申请日：2010-03-17
申请人： Kayvan Najarian , Wenan Chen , Kevin R. Ward
发明人： Kayvan Najarian , Wenan Chen , Kevin R. Ward
IPC分类号： A61B5/00 , G06K9/62 , G06T7/00 , G06T7/42 , G06T7/68 , G06F19/00 , G16H50/20
摘要： A decision-support system and computer implemented method automatically measures the midline shift in a patient's brain using Computed Tomography (CT) images. The decision-support system and computer implemented method applies machine learning methods to features extracted from multiple sources, including midline shift, blood amount, texture pattern and other injury data, to provide a physician an estimate of intracranial pressure (ICP) levels. A hierarchical segmentation method, based on Gaussian Mixture Model (GMM), is used. In this approach, first an Magnetic Resonance Image (MRI) ventricle template, as prior knowledge, is used to estimate the region for each ventricle. Then, by matching the ventricle shape in CT images to the MRI ventricle template set, the corresponding MRI slice is selected. From the shape matching result, the feature points for midline estimation in CT slices, such as the center edge points of the lateral ventricles, are detected. The amount of shift, along with other information such as brain tissue texture features, volume of blood accumulated in the brain, patient demographics, injury information, and features extracted from physiological signals, are used to train a machine learning method to predict a variety of important clinical factors, such as intracranial pressure (ICP), likelihood of success a particular treatment, and the need and/or dosage of particular drugs.

8. 发明授权

US10223800B2 Determine presence of quasi-periodic two-dimensional object 有权
公开(公告)号：US10223800B2
公开(公告)日：2019-03-05
申请号：US15300074
申请日：2014-03-28
申请人： Hewlett-Packard Development Company, L.P.
发明人： Robert Ulichney , Matthew D Gaubatz , Stephen Pollard
IPC分类号： G06T7/42 , G06K9/52 , G06T7/11 , G06K9/62
摘要： Examples disclosed herein relate to determining the presence of quasi-periodic two-dimensional object. In one implementation, a processor determines peak points of a DFT of an image where the peak points are points with a value above a threshold relative to surrounding points. The processor may then output information indicating the existence of a quasi-periodic two-dimensional object within the image based on the peak points.

9. 发明授权

US10096124B2 Water droplet detection device, and three-dimensional object detection device using water droplet detection device 有权
公开(公告)号：US10096124B2
公开(公告)日：2018-10-09
申请号：US14410585
申请日：2013-07-24
申请人： Nissan Motor Co., Ltd. , Clarion Co., Ltd.
发明人： Yasuhisa Hayakawa , Osamu Fukata , Masayuki Takemura , Akira Utagawa , Shoji Muramatsu , Kota Irie
IPC分类号： G06T7/20 , B60S1/08 , G06T7/42 , G06T7/00 , H04N7/18 , B60S1/56 , H04N5/359 , G08G1/16 , G06T7/73 , G06T7/174 , G06T7/254 , G06K9/00
摘要： A water droplet detection device has an image capturing unit and a water droplet detection unit. The image capturing unit has a photographic optical system that an area captures an image of a predetermined area. The water droplet detection unit sets an arbitrary attention point in the captured image, a plurality of first reference points inside an imaginary circle of a predetermined radius having the attention point as a center the imaginary circle, and a plurality of second reference points corresponding to the first reference points outside the imaginary circle. The water droplet detection unit detects edge information between the first reference points and second reference points, and assesses a circularity strength of the edge information to detect a water droplet attached to the photographic optical system. The water droplet detection device can be used with an image conversion unit to form a three-dimensional object detection device.

10. 发明授权

US10037594B2 Resolution estimating device 有权
公开(公告)号：US10037594B2
公开(公告)日：2018-07-31
申请号：US15035337
申请日：2014-12-02
申请人： Sharp Kabushiki Kaisha
发明人： Yoshimitsu Murahashi , Masaaki Moriya
IPC分类号： G06T3/40 , G06T7/42
CPC分类号： G06T3/4007 , G06T7/42 , G06T2207/10004 , G06T2207/20004
摘要： A resolution estimating device is achieved which is capable of adequately estimating the resolution of the original image of any received image signal. A resolution estimating device (1000) includes a proximity-degree acquiring unit (1), an accumulation unit (2), a frequency transform unit (3), and a spectrum analyzing unit (4). The proximity-degree acquiring unit (1) acquires the proximity degree value of each target pixel. The accumulation unit (2) accumulates the proximity degrees of the target pixels, for example, in the vertical direction on the image, and obtains a one-dimensional data sequence of the accumulated proximity degree values. The frequency transform unit (3) performs a frequency transform on the one-dimensional data sequence of the accumulated proximity degree values obtained by the accumulation unit (2), and obtains a one-dimensional frequency-component data sequence which is a one-dimensional data sequence for frequency regions. The spectrum analyzing unit (4) detects periodicity, for example, in the horizontal direction on a proximity degree image on the basis of the one-dimensional frequency-component data sequence obtained by the frequency transform unit (3), and estimates the resolution of the original image, which is an image before a scaling-up process, of an input image on the basis of the detected periodicity.

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