A Survey on Different Relevance Feedback Techniques in Content Based Image Retrieval

The conventional image retrieval methods like Google, Bingo, Yahoo are based on the on textual annotation of images to access the large collection of relevant database images. Then Content Based Image Retrieval (CBIR) is a technique, which takes visual contents of image to retrieve relevant images from large databases. In Content Based Image Retrieval, there is a semantic gap between the low level features and high level semantic concepts. Different relevance feedback techniques bridge this semantic gap. In this paper analyse different subspace learning based relevance feedback algorithm to retrieve images.