scholarly journals Full-color computer-generated hologram using wavelet transform and color space conversion

2019 ◽  
Vol 27 (6) ◽  
pp. 8153 ◽  
Author(s):  
Shota Yamada ◽  
Tomoyoshi Shimobaba ◽  
Takashi Kakue ◽  
Tomoyoshi Ito
Keyword(s):  
Wavelet Transform ◽  
Color Space ◽  
Color Space Conversion ◽  
Computer Generated Hologram ◽  
Full Color ◽  
Color Computer

Color computer-generated hologram generation using the random phase-free method and color space conversion

2016 ◽  
Vol 55 (15) ◽  
pp. 4159 ◽  
Author(s):  
Tomoyoshi Shimobaba ◽  
Michał Makowski ◽  
Yuki Nagahama ◽  
Yutaka Endo ◽  
Ryuji Hirayama ◽  
...  
Keyword(s):  
Random Phase ◽  
Color Space ◽  
Color Space Conversion ◽  
Computer Generated Hologram ◽  
Color Computer

Acceleration of color computer-generated hologram from RGB–D images using color space conversion

2015 ◽  
Vol 340 ◽  
pp. 121-125 ◽  
Author(s):  
Daisuke Hiyama ◽  
Tomoyoshi Shimobaba ◽  
Takashi Kakue ◽  
Tomoyoshi Ito
Keyword(s):  
Color Space ◽  
Color Space Conversion ◽  
Computer Generated Hologram ◽  
Color Computer

scholarly journals Calculation reduction method for color digital holography and computer-generated hologram using color space conversion

2014 ◽  
Vol 53 (2) ◽  
pp. 024108 ◽  
Author(s):  
Tomoyoshi Shimobaba ◽  
Yuki Nagahama ◽  
Takashi Kakue ◽  
Naoki Takada ◽  
Naohisa Okada ◽  
...  
Keyword(s):  
Digital Holography ◽  
Reduction Method ◽  
Color Space ◽  
Color Space Conversion ◽  
Computer Generated Hologram

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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