Title :
Image Auto-Annotation and Retrieval Using Saliency Region Detecting and Segmentation Algorithm
Author :
Chen, He ; Wang, Ruomei
Author_Institution :
Sch. of Inf. Sci. & Technol., Sun Yat-Sen Univ., Guangzhou, China
Abstract :
Automatically assigning one or more relevant keywords to image has important significance. It is easier for people to retrieve and understand large collections of image data. Recent years much research has focused upon this field. In this paper, we introduce a salient region detection and segmentation algorithm used for image retrieval and keywords auto-annotation. We investigate the properties of a bin-cross bin metric between two feather-vectors called the Earth Mover´s Distance (EMD), to enhance the precision and recall performance. The EMD is based on a solution to the transportation problem from linear optimization. It is more robust than histogram matching techniques. In this paper we only focus on applications about color-feathers, and we compare the performances about image auto-annotation and retrieval between EMD and other histogram matching distances. The results indicate that our methods are more flexible and reliable.
Keywords :
distance measurement; image colour analysis; image retrieval; image segmentation; object detection; probability; Earth mover distance; bin-cross bin metric; color-feathers; feather-vectors; image auto-annotation; image retrieval; keywords auto-annotation; linear optimization; saliency region detecting algorithm; saliency region segmentation algorithm; transportation problem; Feature extraction; IEEE Computer Society; Image color analysis; Image retrieval; Image segmentation; Measurement; Visualization; auto-annotation; earth mover´s distance; image retrieval; salient region detection;
Conference_Titel :
Digital Home (ICDH), 2012 Fourth International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1348-3
DOI :
10.1109/ICDH.2012.72