Name
Title | ||
|---|---|---|
Color sensors and their applications based on real-time color image segmentation for cyber physical systems |
Abstract | ||
|---|---|---|
Color information plays an important role in the color image segmentation and real-time color sensor, which affects the result of video image segmentation and correct real-time temperature value. In this paper, a novel real-time color image segmentation method is proposed, which is based on color similarity in RGB color space. According to the color and luminance information in RGB color space, the dominant color is determined at first, and then color similarity can be calculated with the proposed calculation method of color component, which creates a color-class map. Next, the information of the corresponding color-class map is utilized to classify the pixels. Due to the characteristic that thermal inks feature color values that change in real time as the temperature changes, the segmentation results of thermal ink can be used as a real-time color sensor. Then, we also propose a method of color correction and light source compensation for the sake of potential inaccuracy of its measures. We discuss the proposed segmentation method application combining with color sensor (thermal ink) in real-time color image segmentation for Cyber physical system (CPS) by the application in fire detection and summarize a new method in identifying fire in a video based on these characteristics. The experiments showed that the proposed method in vision-based fire detection and identification in videos was effective; the results were accurate and can be used in real-time analysis. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13640-018-0258-x | EURASIP Journal on Image and Video Processing |
Keywords | Field | DocType |
Video image segmentation,Color sensor,Color similarity,Thermal ink,Real-time systems,Cyber physical system,Fire detection and identification | Computer vision,Pattern recognition,Computer science,Segmentation,RGB color space,Image segmentation,Color correction,Pixel,Artificial intelligence,Biometrics,Luminance,Fire detection | Journal |
Volume | Issue | ISSN |
2018 | 1 | 1687-5281 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neal N. Xiong | 1 | 0 | 0.34 |
| yang shen | 2 | 13 | 6.89 |
| Kangye Yang | 3 | 0 | 0.34 |
| Changhoon Lee | 4 | 123 | 15.40 |
| Chunxue Wu | 5 | 25 | 8.85 |