Synthesis of Near-regular Natural Textures
This work addresses texture synthesis and defect detection in computer graphics and vision, but it appears incremental as it builds on existing methods for specific texture types.
The paper tackled texture synthesis for near-regular natural textures by extracting a representative periodic pattern and analyzing local vs. global statistics, resulting in an algorithm validated through experiments with synthetic textures that preserved regularity and visual appearance.
Texture synthesis is widely used in the field of computer graphics, vision, and image processing. In the present paper, a texture synthesis algorithm is proposed for near-regular natural textures with the help of a representative periodic pattern extracted from the input textures using distance matching function. Local texture statistics is then analyzed against global texture statistics for non-overlapping windows of size same as periodic pattern size and a representative periodic pattern is extracted from the image and used for texture synthesis, while preserving the global regularity and visual appearance. Validation of the algorithm based on experiments with synthetic textures whose periodic pattern sizes are known and containing camouflages / defects proves the strength of the algorithm for texture synthesis and its application in detection of camouflages / defects in textures.