Non-photorealistic rendering (NPR) technique combines artistic painting rule and scientific methods. This technique can express and transfer information besides photorealistic computer graphics. The NPR also serves an increasingly important role in medical science

architectonic

and education. Many artworks

such as oil

watercolor

and Chinese calligraphy

have recently been simulated. Although numerous NPR methods have been proposed to digitize and simulate artistic works

the exploration or rendering of different artistic works remains extremely challenging and an open question. A few NPR methods can be adopted to render chalk art style. This study proposes an NPR technique that generates a chalk art style from a 2D photograph on the basis of diffusion and line integral convolution (LIC). Similar to existing exemplar-based methods

an input natural image is regarded as a foreground image

and an input material image is taken as a background image. We obtain the final chalk art painting through the foreground image mapping to the background image. First

continuous and smooth edge information is obtained by threshold processing and edge extraction from the target image. The edge detection method is based on the difference of the Gaussian filter. Considering that the real chalk art painting has coarse lines

we adopt the diffusion technique to simulate this characteristic. Image enhancement is also used to enhance the details of the edge information. Second

when people create a chalk painting

they usually use chalk to draw on the blackboard or other materials; the chalk pigment will then be absorbed on these materials to show some artistic illustration. Therefore

this textural characteristic of the chalk stroke should be simulated in the system. Our algorithm adds some white noise to the target image

and the chalk brush texture is simulated based on the LIC. The morphological dilation operation is used to generate the final chalk stroke texture. The real artistic effect of the chalk painting is often created in blackboard

wood

and other materials. Thus

the blackboard image is input as the background image. Based on the layer-mapping technique

the algorithm will merge the brush texture image

color image

and edge image to the blackboard image. Subsequently

the final chalk painting art style will be simulated. We can obtain chalk art illustrations by inputting different source images. The line details and stroke texture of the chalk characteristic can also be displayed. When the different foreground images and background images are input

different chalk illustrations can be obtained. This study proposes an NPR method to generate chalk art style. Experimental results demonstrate the effectiveness of our method in producing chalk line stylistic illustrations. This chalk painting art style is a useful supplement to the NPR

and the rendering results advance the NPR field. People without painting experience can create chalk art painting through our simple system. The proposed method is simple

fast

and easy to implement.