Several content based image retrieval systems use region-based descriptors of salient regions to represent the image content. In this application domain, no perfect pixel wise segmentation is required, but instead, a stable and unsupervised extraction of salient region-descriptors is needed which might be generally applicable. Accordingly, in this paper an algorithm is proposed which combines l...

Human eye is perceptually more sensitive to certain colors and intensities and objects with such features are considered more salient. Detection of Salient image regions is useful in applications such as object based image retrieval, adaptive content delivery, adaptive region-of interest based image compression, and smart image resizing .This problem can be handled by mapping the pixels into va...

In content-based image retrieval, the representation of local properties in an image is one of the most active research issues. This paper introduces a salient region detector based on wavelet transform. The detector can extract the visually meaningful regions on an image and reflect local characteristics. An annular segmentation algorithm based on the distribution of salient regions is designe...

Image classification is one disposal procedure for high level semantic analysis, e.g., image data mining, knowledge discovery and intelligent data analysis. As one image generally contains multiple semantic objects, it’s not appropriate to conduct image classification according the global features. So, image segmentation is a must before image classification. However, accurate semantic segmenta...

A new approach to automatically detect and track salient regions in generic videos is presented in this paper. Specifically, given a starting video frame, we first detect its salient regions based on extracted color and orientation maps; then we track these regions for the rest of frames within a short period of time. The extracted salient region information could be used to evaluate the frame ...

We present an algorithm for graph based saliency computation that utilizes the underlying dense subgraphs in finding visually salient regions in an image. To compute the salient regions, the model first obtains a saliency map using random walks on a Markov chain. Next, k-dense subgraphs are detected to further enhance the salient regions in the image. Dense subgraphs convey more information abo...

In this paper, a novel saliency theory based RR-IQA metric is introduced. As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. In order to extract the salient regions, we use blob decomposition (BD) tool as a texture component descriptor. A new method for blob decomposition is propos...