نویسندگان
دانشگاه رازی کرمانشاه - دانشکده مهندسی - گروه کامپیوتر
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Image-based search is one of the most applied issues in computer vision. In the past decades, content based image retrieval (CBIR) systems using one query or multiple queries with the same semantic information were well investigated. In contrast, the CBIR systems based on multiple queries with different semantics have rarely considered in the literature. This article presents a novel framework in order to combine the content of multiple queries for image retrieval. The proposed framework introduces several new search operators. The proposed approach comprises four stages: in the first stage, for each issued query, a retrieval process based on low-level features is applied and according to the results, a binary component vector is automatically computed for each issued query. This vector corresponds to regions and salient objects inside the query image. The vectors are then combined by logical operators to generate one binary component vector. In the third and fourth stages, retrieving and showing results are performed based on the binary component vector, respectively. The remarkable advantages of the proposed method are to efficiently combine different images for retrieval purposes; also it decreases complicated and time-consuming computations as well as simplifying the implementation of several search operators. The operators correspond to the set theory and known logical operators. The experimental results distinctly exhibit the effectiveness of the proposed method. In comparison to the previous methods, it improves 27% of the performance achievement.
کلیدواژهها [English]
)