This paper presents a new hybrid approach for detecting salient objects in an image. It consists of two processes: local saliency estimation and global-homogeneity refinement. We model the salient object detection problem as a region growing and competition process by propagating the influence of foreground and background seed-patches. First, the initial local saliency of each image patch is me...

. Automatic liver segmentation plays an important role in computer-aided diagnosis and treatment. Manual segmentation of organs is a difficult and tedious task and so prone to human errors. In this paper, we propose an adaptive 3D region growing with subject-specific conditions. For this aim we use the intensity distribution of most probable voxels in prior map along with location prior. We als...

Text in images and video frames carries important information for visual content understanding and retrieval. In this paper, by using multiscale wavelet features, we propose a novel coarse-to-fine algorithm that is able to locate text lines even under complex background. First, in the coarse detection, after the wavelet energy feature is calculated to locate all possible text pixels, a density-...

In this paper we present a colour segmentation method based on a normalized colour naming algorithm which removes the effects of the varying conditions due to changes in scene illuminant. Images labelled with the colour name and intensity of small regions are further processed by a region growing step providing a sound segmentation. The method has been tested on a large set of images we get fro...

This paper presents a novel method MGARS to automatic road area segmentation based on motion and gray feature for the purpose of urban traffic surveillance. The proposed method can locate road region by region growing algorithm with the fusion feature of motion information and grayscale of background image, which is independent to road marker information. An adaptive background subtraction appr...