Background Self-adapted Digital Camouflage Pattern Generation Algorithm for Fixed Target

Digital pattern painting is currently a hot topic in camouflage research. This paper presents a modified digital camouflage pattern generation algorithm for fixed target. The color characteristics of the background were extracted by K-means clustering algorithm and the characteristics of the background spots were counted. By filling the dominant color image with colors and blocks, digital pattern paintings were automatically generated. The characteristics such as the dominant color and the size of the digital unit were extracted from the background image, so the constraints of the algorithm can be automatically changed according to the background image. The experimental results show that the digital camouflage pattern generated by the presented algorithm fits the background image in color and spots with good camouflage effect.