The texture is a two-and three-dimensional design element that is distinguished by the visual and physical properties perceived. Textured areas in the image can be marked with uniform or varying spatial intensity distribution. There are many techniques and methods from simple to sophisticated which available including machine learning-based methods to modify the texture map. The texture feature description becomes a new challenge in the field of computer vision and pattern recognition since the emergence of the local pattern binary method (LBP). This study proposes a new method called Local Weighting Pattern (LWP) for modifying textures based on the pixel's neighborhood of an RGB image. The results of this study obtained that LWP method produces a texture with a unique and artistic visualization. The Log function has been used to improve the image quality of the LWP method.
A mosaic is a combination of two or more images with various combining techniques. One of the computer graphics applications is the image mosaic used for various purposes such as texture maps and better image backgrounds. One of the important things in making image mosaic is how to create small pieces of the image in such a way that it produces a good image mosaic. A number of methods have been proposed to build an image mosaic system that produces good mosaic results, but it usually requires complicated calculations. Fuzzy image processing is a form of information processing that input and output both images. This is a collection of fuzzy approaches that understand, represent and process their images, segments, and features as a fuzzy set. In this study, fuzzy image processing concept is used to create image mosaic by random seed generation using Fuzzy Membership Function (MF).
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