Copper plate color change technology
By analyzing the characteristics and application scope of the commonly used segmentation algorithms, it is concluded that the current segmentation algorithms can not be directly applied to the segmentation process. Which combines the color feature and discoloration corrosion area and brightness characteristics to the completion of the copper surface discoloration and corrosion area segmentation.
For copper image color quantization processing, design a new algorithm based on color quantization clustering. The algorithm classifies the color of the image in HSI color space and determines the initial clustering center, then converts to the RGB color space, and combines the K mean algorithm to solve the final clustering center. In order to complete the process of color quantization copper image. The experimental results show that the algorithm not only has ideal quantization effect, but also preserves the detail and layering of the image.
With the rapid development and progress of image processing technology, its application scope is more and more widespread. Such as in industry, agriculture, medicine, aviation and other fields have a large number of applications. In order to detect whether the occurrence of copper surface discoloration and corrosion, discoloration and corrosion of the extraction of accurate and precise calculation of the regional area, this paper will take the coins in circulation in the copper coins (hereinafter refer to chapter said copper copper coins) as the research object. Through the analysis and research of a large number of coin image, thus put forward a set of schemes based on image processing technology of copper surface discoloration and corrosion area extraction.
