According to the image features and the related experimental results

a temperature indicating paint(TIP) image segmentation algorithm based on fuzzy C-means (FCM) clustering was proposed. Taking the FCM clustering algorithm as the core

the algorithm employed the bilateral filter to smooth the image to improve the segmentation quality. The color space conversion was used to improve the iterative efficiency of the image clustering. Experiments showed that the algorithm can enhance the feature information needed in the process of the interpretation of the TIP. The algorithm can extract isotherms that cant be recognized by naked eye and the temperature measurement error was ±10℃. The algorithm has good application effect and meets the engineering requirements

so it has been applied to the development of automatic interpretation software for TIP.