Image retrieval using fractal feature
Shou-Cheng Hsiung, Jyh-Horng Jeng · Annual Conference on Computers · 2005
Content-based image retrieval attracted many researchers of various fields in an effort to automate data analysis and indexing. In contemporary image databases one finds many images with the same content perturbed by zooming, scaling, rotation and noise. For the purpose of image recognition in such databases we employ features based on statistics stemming from fractal transforms of gray-scale images through fractal image compression. Experimental results show that the fractal features derived from these statistical aspects can be made robust subject to perturbations.