Design of variable and adaptive fractional order FIR differentiators
Signal Processing - Fractional calculus applications in signals and systems
A smart content-based image retrieval system based on color and texture feature
Image and Vision Computing
Image Retrieval System Based on Adaptive Color Histogram and Texture Features
The Computer Journal
Content-based image retrieval using color and texture fused features
Mathematical and Computer Modelling: An International Journal
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This paper introduces a texture features extraction technique for content-based image retrieval using fractional differential operator mask convolution with Ces$#225;ro means. We propose one general fractional differential mask on eight directions for texture features extraction. Image retrieval based on texture features is getting unusual concentration because texture is an important feature of natural images. Experiments show that, the capability of texture features extraction by fractional differential-based approach appears efficient to find the best combination of relevant retrieved images for different resolutions. To compare the performance of image retrieval method, average precision and recall are computed for query image. The results showed an improved performance (higher precision and recall values) compared with the performance using other methods of texture extraction.