We propose a flexible image stylisation system for reforming a source image into a
stained-glass style or some other style desired by users. It consists of three stages including image segmentation, colour or texture allocation and synthesis of calmes. Each stage provides some options for users to choose from. The system provides three options of image
segmentation for the users to choose from, including automatic, semi-automatic and manual image segmentation. The automatic option randomly generates seeds in the image region, calculates the distance between each seed and each pixel and then assigns each pixel to the nearest seed region to accomplish image segmentation. The semi-automatic one segments the image according to the seeds provided by the user. The user then repeatedly adjusts the result by deleting or adding some seeds. The last version involves manual image segmentation performed by the users. The next step in segmentation is colour or texture allocation. Each segmented region is allocated with the colour or texture of reference images chosen from a pre-built database. The proposed system provides many options for this allocation, allowing the users to select from a variety of methods of texture or colour allocation. A unique feature of stained glass is that it is held together with lead, zinc, brass or copper strips called calmes. We use a back-propagation neural network to train a calme generator using an image of line drawing as the input together with an image of the corresponding calme of the line drawing as the output. The users can choose whether or not to put the synthesised calmes on the resulting images. The proposed system is easy to use and very flexible. It provides many options for users to stylise an image into a variety of stylised results. Our experiments show that the proposed system can generate a wide range of satisfactory results.