Content-Based Rotary Kiln Flame Image Retrieval

In this paper, a content-based image retrieval system for rotary kiln flame image (CBIR-RKFI) is introduced for the purpose of making good use of rotary kiln flame images. It calculates the texture and fire & clinker features of the flame image, then, through the similarities comparison, it returns a set of original retrieval results. Moreover, with the users’ relevant feedbacks, it optimizes the final retrieval results. A prototype system was realized based on the rotary kiln image database that contained more than 500 rotary kiln flame images (Sampled in an alumina rotary kiln). Retrieval experiments with different features were carried out. The results demonstrate the effectiveness of the retrieval methods, and among them, the integrated features based method has the highest precision (84%). The research can provide strong support for modern rotary kiln supervision and management.