Efficient Color Space Conversion using Custom Instruction in a RISC Processor

2007 ◽  
Author(s):  
Muhammad Bilal ◽  
Shahid Masud
Keyword(s):  
Color Space ◽  
Custom Instruction ◽  
Color Space Conversion ◽  
Risc Processor

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.

Efficient RGB to YCbCr Color Space Conversion for Embedded Application

2014 ◽  
Vol 543-547 ◽  
pp. 2873-2878
Author(s):  
Hui Yong Li ◽  
Hong Xu Jiang ◽  
Ping Zhang ◽  
Han Qing Li ◽  
Qian Cao
Keyword(s):  
Direct Method ◽  
Color Space ◽  
Video Data ◽  
Floating Point ◽  
Portable Devices ◽  
Embedded Processor ◽  
Color Space Conversion ◽  
Ycbcr Color Space ◽  
Original Approach ◽  
General Method

Modern embedded portable devices usually have to deal with large amounts of video data. Due to massive floating-point multiplications, the color space conversion is inefficient on the embedded processor. Considering the characteristics of RGB to YCbCr color space conversion, this paper proposed a strategy for truncated-based LUT Multiplier (T-LUT Multiplier). On this base, an original approach converting RGB to YCbCr is presented which employs the T-LUT Multiplier and the pipeline-based adder. Experimental results demonstrate that the proposed method can obtain maximum operating frequency of 358MHz, 3.5 times faster than the direct method. Furthermore, the power consumption is less than that of the general method approximately by 15%~27%.

A Robustness Watermarking Algorithm for Digital Color Image Print-Scan Process

2013 ◽  
Vol 333-335 ◽  
pp. 992-997
Author(s):  
Yun Lu Ge ◽  
Hui Han ◽  
Xiao Dong Sun ◽  
Sheng Pin Wang ◽  
Sheng Yun Ji
Keyword(s):  
Color Image ◽  
Random Noise ◽  
Color Space ◽  
Low Frequency ◽  
New Method ◽  
Color Spaces ◽  
Image Watermark ◽  
Color Space Conversion ◽  
Frequency Components ◽  
Orthogonal Transform

Most of watermarking algorithms are for digital grey image, which are not robust against the attacks of print-scan process, and the embedded information capacity is small. To solve these problem, a new method based on DWT transform and Walsh orthogonal transform for the print-scan process of digital color image was proposed. The method chosed the color spaces conversion from RGB to CIEL*a*b* for digital color image. The low frequency components of the DWT transform image was embed the watermark. The results show that the correlation of watermark is improved using Walsh orthogonal transform, the watermark extraction rate is high and image watermark is distinct and readable after print-scan process. And this method is robust against the various attacks of the print-scan process, such as color space conversion, image halftone, D/A conversion, A/D conversion, scaling, rotation, cropping, skew, and random noise signals.

Implementation of RGB to HSV Color Space Conversion with Xilinx System Generator

2013 ◽  
Vol 816-817 ◽  
pp. 527-534 ◽  
Author(s):  
Long Wen ◽  
Cheng Xu ◽  
Tao Li ◽  
Zheng Tian
Keyword(s):  
Color Space ◽  
Design Tool ◽  
Color Model ◽  
Hsv Color Space ◽  
System Generator ◽  
Color Space Conversion ◽  
Field Programmable ◽  
C Program ◽  
Xilinx System Generator ◽  
Program Experiment

The HSV (Hue, Saturation, and Value) color model is more intuitive than the RGB color model and widely used in color recognition and color space segmentation. Currently as the requirements of high processing speed and special applications need to realize RGB to HSV color space conversion, in this paper a new Field Programmable Gate Array (FPGA) architecture named RGB2HSV module was developed via an accurate and visible FPGA implementation method in use of Xilinx System Generator (XSG). XSG is a design tool in Simulink of MATLAB which accelerates design by providing access to highly parameterized intellectual blockset for Xilinx FPGA. In this paper simulation test images were used to measure the deviation and the time consume by the RGB2HSV module and relevant C program. Experiment shows that the maximum frequency can reach 121.433MHz and lower deviation was achieved in Xilinx Zynq xc7z020 device. The full-pipelined and parallel RGB2HSV module had been adapted in order to speed up the RGB to HSV color space conversion and took as much as 87% less than that of C program in our experiment.

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