Region-Based Image Interpretation and Recall

In this paper, we present an approach to primarily achieve the semantic interpretation and the region retrieval for an attentive region in a color image. The main components of the system include image feature extraction, indexing process, as well as linguistic inference rules construction and semantic description. Based on these features, each of attentive regions in an image can be described by a global linguistic meaning. The main procedure consists of two parts: forward and recall processes. The forward process primarily performs the linguistic meaning description of objects for an image, and the recall process reconstructs the region image which is the rough mental image of human memory retrieval. Experiments confirm that our approach is reasonable and feasible. bership function) to construct a knowledge base such as human knowledge and experiences [ I , 21. A useful data information may be presented by the fuzzy number, and the data presentation of a fuzzy number can be parameterized to simplify the fizzy computation. In accordance with the advantages of indexing process and fuzzy set theory, in this paper, we present an approach to perform a human-based image interpretation. This approach combines image features and linguistic database to describe semantic meaning for image region.