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公开(公告)号：US20190303645A1
公开(公告)日：2019-10-03
申请号：US15960559
申请日：2018-04-24
Applicant: Industrial Technology Research Institute
Inventor： Wen-Hung Ting , Hian-Kun Tenn , Duan-Li Liao , Chia-Chang Li , Po-Lung Chen
IPC: G06K9/00
Abstract: An electronic device, an iris recognition method and a non-volatile computer-readable medium are provided. A processor in the electronic device obtains a first and second iris images, and calculates a plurality of first and second feature mark boxes that are non-uniformly arranged according to the first and second iris images. The processor uses the first feature mark boxes to obtain a first and second image features from the first and second iris images respectively, and compares the first and second image features to obtain a first recognition result. The processor uses the second feature mark boxes to obtain a third and fourth image features from the second and first iris images respectively, and compares the third and fourth image features to obtain a second recognition result. The processor determines a similarity degree of the first and second iris images according to the first and second recognition results.
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Patent Agency Ranking
公开(公告)号：US11238624B2
公开(公告)日：2022-02-01
申请号：US16808345
申请日：2020-03-03
Applicant: Industrial Technology Research Institute
Inventor： Duan-Li Liao , Chia-Chang Li , Wen-Hung Ting , Po-Lung Chen
Abstract: Provided are an image transform method and an image transform network. The method is for the image transform network including an image generator, a transform discriminator and a focus discriminator, and includes: generating a transformed image according to an un-transformed image and focus information by the image generator; computing a transform discrimination value according to the transformed image by the transform discriminator; computing a value of a first generator loss function and updating the image generator by the image generator; generating a focus discrimination value according to the un-transformed image, the transformed image, and the focus information by the focus discriminator; and computing a value of a second generator loss function according to the focus discrimination value and updating the image generator according to the value of the second generator loss function by the image generator.
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公开(公告)号：US20210118195A1
公开(公告)日：2021-04-22
申请号：US16808345
申请日：2020-03-03
Applicant: Industrial Technology Research Institute
Inventor： Duan-Li Liao , Chia-Chang Li , Wen-Hung Ting , Po-Lung Chen
Abstract: Provided are an image transform method and an image transform network. The method is for the image transform network including an image generator, a transform discriminator and a focus discriminator, and includes: generating a transformed image according to an un-transformed image and focus information by the image generator; computing a transform discrimination value according to the transformed image by the transform discriminator; computing a value of a first generator loss function and updating the image generator by the image generator; generating a focus discrimination value according to the un-transformed image, the transformed image, and the focus information by the focus discriminator; and computing a value of a second generator loss function according to the focus discrimination value and updating the image generator according to the value of the second generator loss function by the image generator.
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公开(公告)号：US09117138B2
公开(公告)日：2015-08-25
申请号：US13726454
申请日：2012-12-24
Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE
Inventor： Chia-Chang Li , Duan-Li Liao
CPC classification number: G06K9/4604 , G06K9/00375 , G06T7/73 , G06T2207/10028 , G06T2207/30196
Abstract: According to an exemplary embodiment, a method for object positioning by using depth images is executed by a hardware processor as following: converting depth information of each of a plurality of pixels in each of one or more depth images into a real world coordinate; based on the real world coordinate, computing a distance of each pixel to an edge in each of a plurality of directions; assigning a weight to the distance of each pixel to each edge; and based on the weight of the distance of each pixel to each edge and a weight limit, selecting one or more extremity positions of an object.
Abstract translation: 根据示例性实施例，通过使用深度图像的对象定位的方法由硬件处理器执行如下：将一个或多个深度图像中的每一个中的多个像素中的每一个的深度信息转换为真实世界坐标; 基于所述真实世界坐标，计算每个像素与多个方向中的每个方向上的边缘的距离; 将每个像素的距离分配给每个边缘; 并且基于每个像素到每个边缘的距离的权重和重量限制，选择对象的一个或多个末端位置。
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公开(公告)号：US10890979B2
公开(公告)日：2021-01-12
申请号：US15959665
申请日：2018-04-23
Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE
Inventor： Duan-Li Liao , Chia-Chang Li , Wen-Hung Ting , Hian-Kun Tenn
IPC: G06F3/01 , G06K9/00 , G06F16/532 , G06T7/13
Abstract: A controlling system and a controlling method for virtual display are provided. The controlling system for virtual display includes a visual line tracking unit, a space forming unit, a hand information capturing unit, a transforming unit and a controlling unit. The visual line tracking unit is used for tracking a visual line of a user. The space forming unit is used for forming a virtual display space according to the visual line. The hand information capturing unit is used for obtaining a hand location of the user's one hand in a real operation space. The transforming unit is used for transforming the hand location to be a cursor location in the virtual display space. The controlling unit is used for controlling the virtual display according to the cursor location.
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公开(公告)号：US10474893B2
公开(公告)日：2019-11-12
申请号：US15960559
申请日：2018-04-24
Applicant: Industrial Technology Research Institute
Inventor： Wen-Hung Ting , Hian-Kun Tenn , Duan-Li Liao , Chia-Chang Li , Po-Lung Chen
IPC: G06K9/00
Abstract: An electronic device, an iris recognition method and a non-volatile computer-readable medium are provided. A processor in the electronic device obtains a first and second iris images, and calculates a plurality of first and second feature mark boxes that are non-uniformly arranged according to the first and second iris images. The processor uses the first feature mark boxes to obtain a first and second image features from the first and second iris images respectively, and compares the first and second image features to obtain a first recognition result. The processor uses the second feature mark boxes to obtain a third and fourth image features from the second and first iris images respectively, and compares the third and fourth image features to obtain a second recognition result. The processor determines a similarity degree of the first and second iris images according to the first and second recognition results.
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