2019/04/10 by Ushasi Chaudhuri, Chaudhuri, Ushasi, Partha Bhowmick +3
Computer Science · #Advanced Image and Video Retrieval Techniques #Artificial intelligence #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Data mining #FOS: Computer and information sciences #Feature (linguistics) #Image (mathematics) #Image Processing and 3D Reconstruction #Image Retrieval and Classification Techniques #Image retrieval #Information retrieval #Logo (programming language) #Logos Bible Software #Pattern recognition (psychology) #Polygon (computer graphics) #Representation (politics) #Rough set #Set (abstract data type) #Task (project management) #Trademark #cs.CV
paper · pdf · doi:10.48550/arxiv.1904.05008
arxiv created 2019/04/10 · openalex publication_date 2019/04/10 · arxiv updated 2019/04/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Searching for similar logos in the registered logo database is a very important and tedious task at the trademark office. Speed and accuracy are two aspects that one must attend to while developing a system for retrieval of logos. In this paper, we propose a rough-set based method to quantify the structural information in a logo image that can be used to efficiently index an image. A logo is split into a number of polygons, and for each polygon, we compute the tight upper and lower approximations based on the principles of a rough set. This representation is used for forming feature vectors for retrieval of logos. Experimentation on a standard data set shows the usefulness of the proposed technique. It is computationally efficient and also provides retrieval results at high accuracy.