Method of evaluating crosstalk and crosstalk evaluation device performing the same
AssigneeSamsung Display Co., Ltd.
InventorYOUNGSANG HA
Life of this patent
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Abstract
A method of evaluating crosstalk includes receiving a first multi-view 3-dimensional image, a second multi-view 3-dimensional image, and a third multi-view 3-dimensional image, performing a deep learning on a crosstalk evaluation for classifying the first multi-view 3-dimensional image into a normal image or a defective image to generate a learning model, and inputting the third multi-view 3-dimensional image different from the first multi-view 3-dimensional image into the learning model to perform the crosstalk evaluation of the third multi-view 3-dimensional image.
Claims20
A method of evaluating crosstalk, the method comprising:
- receiving a first multi-view 3-dimensional image, a second multi-view 3-dimensional image, and a third multi-view 3-dimensional image;
- performing a deep learning on a crosstalk evaluation for classifying the first multi-view 3-dimensional image into a normal image or a defective image to generate a learning model;
- and
- inputting the third multi-view 3-dimensional image different from the first multi-view 3-dimensional image into the learning model to perform the crosstalk evaluation of the third multi-view 3-dimensional image.
A method of evaluating crosstalk, the method comprising:
- receiving a first multi-view 3-dimensional image, a second multi-view 3-dimensional image, and a third multi-view 3-dimensional image;
- extracting a grayscale of the first multi-view 3-dimensional image;
- performing a deep learning on a crosstalk evaluation for classifying the first multi-view 3-dimensional image into a normal image or a defective image to generate a learning model;
- and
- inputting the third multi-view 3-dimensional image different from the first multi-view 3-dimensional image into the learning model to perform the crosstalk evaluation of the third multi-view 3-dimensional image.
A crosstalk evaluation device comprising:
- a display panel;
- a diffuser screen that reflects a first multi-view 3-dimensional image, a second multi-view 3-dimensional image, and a third multi-view 3-dimensional image provided by the display panel;
- a digital camera that acquires the first multi-view 3-dimensional image, the second multi-view 3-dimensional image, and the third multi-view 3-dimensional image reflected by the diffuser screen;
- and
- a crosstalk evaluator that receives the first multi-view 3-dimensional image, the second multi-view 3-dimensional image, and the third multi-view 3-dimensional image, performs a deep learning on a crosstalk evaluation for classifying the first multi-view 3-dimensional image into a normal image or a defective image to generate a learning model, and inputs the third multi-view 3-dimensional image different from the first multi-view 3-dimensional image into the learning model to perform the crosstalk evaluation of the third multi-view 3-dimensional image.
Dependencies are inferred from the claim text.