Combined Query Based Image Retrieval Using Structure Elements Descriptor
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Similar image retrieval involves identifying and ranking images from a database based on visual attributes such as color, texture, and shape, with the goal of finding those most closely matching a given query image. This task requires precise analysis of image content to achieve accurate results. In this study, we propose an approach that incorporates structural information derived from an image segmentation model. This structural information highlights image characteristics, such as object shapes and their backgrounds, which are not fully captured by traditional dense global descriptors. By combining this structural information with global descriptors, our method captures both detailed shapes and broader image features in a user-controllable manner. Experimental results demonstrate the effectiveness of this integration approach in improving the performance of similarity search tasks.
Abstract
Similar image retrieval involves identifying and ranking images from a database based on visual attributes such as color, texture, and shape, with the goal of finding those most closely matching a given query image. This task requires precise analysis of image content to achieve accurate results. In this study, we propose an approach that incorporates structural information derived from an image segmentation model. This structural information highlights image characteristics, such as object shapes and their backgrounds, which are not fully captured by traditional dense global descriptors. By combining this structural information with global descriptors, our method captures both detailed shapes and broader image features in a user-controllable manner. Experimental results demonstrate the effectiveness of this integration approach in improving the performance of similarity search tasks.