Color CENTRIST: Embedding color information in scene categorization

• A color index scheme is designed to embed color information into the framework of CENTRIST.
• Performance of the proposed descriptor is evaluated based on various datasets.
• Extensive performance comparison with original CENTRIST descriptors, local descriptors, and local patterns.
• An application on object detection is proposed to applying color CENTRIST in different domains.

A new color descriptor has now been proposed to embed color information into the framework of CENsus TRansform hISTogram (CENTRIST), so that such a state-of-the-art visual descriptor can be further improved to categorize image scenes. In the proposed color CENTRIST descriptor, global structure characteristics are described by both gradients derived from intensity values and color variations between image pixels. The spatial pyramid scheme has also been adopted to convey information in different scales. Comprehensive studies based on various datasets were conducted to verify the effectiveness of the color CENTRIST from different aspects, including the way to quantize the color space, selection of color space, and categorization performance on various datasets. We demonstrated that the color CENTRIST descriptor was not only easy to implement, but also reliably achieved superior performance over CENTRIST. An application was also proposed to demonstrate the possibility of applying the color CENTRIST in various domains.