Title :
Study on efficacy of relevance feedback for Content Based Image Retrieval
Author :
Singh, Jasvinder ; Rajpal, Navin
Author_Institution :
GGSIPU, USICT, New Delhi, India
Abstract :
This paper focuses on a very powerful and efficient technique using which Content Based Image Retrieval (CBIR) is being performed. If one drills down to the origin of CBIR, one would come across low level features like shape, color and texture as parameters which have been used to represent images. These low level features allow one to locate images which are generally visually similar. Although, the image retrieval is performed but visually similar images are not mapped to nearby locations. Hence the need arose to create a powerful technique for image retrieval. Thus came into existence relevance feedback. We have performed an exhaustive study on the efficacy of relevance feedback for CBIR from its commencement till present day and have tried to highlight the advancements done so far in this promising technique.
Keywords :
content-based retrieval; image representation; image retrieval; relevance feedback; CBIR; content based image retrieval; image representation; relevance feedback; Algorithm design and analysis; Image retrieval; Kernel; Optimization; Radio frequency; Signal processing algorithms; Training; Biased Discriminant Analysis (BDA); Content Based Image Retrieval (CBIR); Differential Scatter Discriminant Criterion (DSDC); Direct Kernel Biased Discriminant Analysis (DKBDA); Direct Linear Discriminant Analysis (DLDA); Generalized BDA (GBDA); Grey Relational Analysis (GRA); Hierarchical Non parametric Discriminant Analysis (HNDA); Kernel Biased Discriminant Analysis (KBDA); Kernel Direct BDA (KDBDA); Nonparametric Discriminant Analysis (NDA); Relevance Feedback (RF);
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-9-3805-4415-1