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About this paper
Mohammad Rezaei, Ali Ahmadi, Navid Naderi
The Mix Histogram (MH) introduces a low-level image feature descriptor for Content-Based Image Retrieval by integrating quantized color and edge orientation information. This method achieved higher precision and recall in image retrieval experiments on the Corel-5k dataset, outperforming Color Auto-Correlograms and Multi-Texton Histograms.
Key insights
- Combining color distribution with edge orientation provides a more perceptually relevant and discriminative image representation, aligning with human visual processing.
- Using the HSV color space and Zenzo's method for gradient computation on color images helps preserve chromatic information while accurately detecting edge directions.
- Optimal performance is achieved through a specific balance in the quantization of color and edge orientation, indicating that excessive detail can introduce noise rather than improve discrimination.
Summary by alphaXiv.
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