Patents by Inventor TUN-KAI YAO

TUN-KAI YAO has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Image distortion correction method and image distortion correction device using the same
    Patent number: 9165219
    Abstract: An image distortion correction method and an image distortion correction device are provided. The image distortion correction method uses a neural network model to perform a correcting operation on an original image so as to obtain a correction image with plural correction points. Firstly, a position coordinate of the correction point is inputted into the neural network model, so that a first direction coordinate correction amount is outputted from the neural network model. Then, the position coordinate of the correction point is inputted into the neural network model, so that a second direction coordinate correction amount is outputted from the neural network model. Afterwards, a pixel value of the original image corresponding to the first direction coordinate correction amount and the second direction coordinate correction amount is used as a pixel value of the correction point.
    Type: Grant
    Filed: February 7, 2014
    Date of Patent: October 20, 2015
    Assignee: NATIONAL CENTRAL UNIVERSITY
    Inventors: Ching-Han Chen, Tun-Kai Yao
  • IMAGE DISTORTION CORRECTION METHOD AND IMAGE DISTORTION CORRECTION DEVICE USING THE SAME
    Publication number: 20150063685
    Abstract: An image distortion correction method and an image distortion correction device are provided. The image distortion correction method uses a neural network model to perform a correcting operation on an original image so as to obtain a correction image with plural correction points. Firstly, a position coordinate of the correction point is inputted into the neural network model, so that a first direction coordinate correction amount is outputted from the neural network model. Then, the position coordinate of the correction point is inputted into the neural network model, so that a second direction coordinate correction amount is outputted from the neural network model. Afterwards, a pixel value of the original image corresponding to the first direction coordinate correction amount and the second direction coordinate correction amount is used as a pixel value of the correction point.
    Type: Application
    Filed: February 7, 2014
    Publication date: March 5, 2015
    Applicant: National Central University
    Inventors: CHING-HAN CHEN, TUN-KAI YAO