Abstract

Traditional color image segmentation quality control method image segmentation quality is low, the control effect is not good. To solve the above problems, a color image segmentation quality control method based on cloud computing is proposed. This method is composed of five steps: first, color image acquisition architecture is designed, color image storage is completed by using cloud computing, th en cloud image is used to preprocess the collected image (color quantization, color space conversion, color similarity measurement), and th en cloud computing is used for color clustering. Finally, the regions are merged and deleted to achieve color image color consistency control and realize segmentation quality control. The results show that the method can effectively control the quality of color image segmentation, and the consistency, contrast and shape parameters are improved by 0.14, 0.19 and 0.19, respectively(Abstract).

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.