Over the last several years, there has been significant advancement in the molecular characterization of intracranial diseases, particularly cerebral neoplasms. While nuclear medicine technology, including PET/CT, has been at the foreground of exploration, new MR imaging techniques, specifically diffusion-weighted and diffusion tensor imaging, have shown interesting applications towards advanci...

Connected component labeling (CCL) is a key step in image segmentation where foreground pixels are extracted and labeled. Sequential CCL is a computationally expensive operation and thus is often done within parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them NSZ label equivalence (NSZ-LE) method seemed to perform...

Background segmentation is a general technique that aims at detecting the moving objects in a sequence of continuous scenes or video stream by separating the non-moving background from the moving foreground object. The success and weakness of a foreground and/or background segmentation method depends on several external factors such as the scene selection, lighting, and weather conditions. Henc...

Foreground and background features are focused (or defocused) diierently in an image because corresponding objects are at diierent depths in the scene. This paper presents a novel approach for segmenting foreground and background in video images based on feature defocus. A modiied defocus measurement that distinguishes between high-contrast defocused edges and low-contrast focused edges is pres...

Many existing color based image search techniques searches image based on color of entire image irrespective of foreground and background which have disadvantage of retrieving images based on dominant color in the image (mostly background) but many a time user might be interested in foreground information. We are focusing on image search based on foreground color. Obviously since locating objec...

Salient object detection has gradually become a popular topic in robotics and computer vision research. This paper presents a real-time system that detects salient object by integrating objectness, foreground and compactness measures. Our algorithm consists of four basic steps. First, our method generates the objectness map via object proposals. Based on the objectness map, we estimate the back...

Detecting moving pedestrians and vehicles with foreground segmentation algorithms is problematic during fluctuating lighting conditions. Edge-based approaches are more robust to lighting than the conventional intensity-based ones. The issue with edge-based approaches though is segmenting the internal foreground areas. In this work a strategy is developed to detect complete foreground areas. Fir...

This paper deals with the extraction and characterization of foreground objects in video sequences. The algorithm first computes the mosaic image representing the background information and then extracts foreground objects. In this last step, the foreground objects are progressively extracted taking into account the reliability of the contour information. This extraction step is based on morpho...