Optic Disc (OD) detection is a key pre processing component in many algorithms designed for automatic extraction of retinal anatomical structures and lesions thus, reliable and efficient OD localization is significant tasks in ophthalmic image processing. We aim to investigate the relevance of computational saliency model in retinal images in the context of OD detection. The optic disc in a ret...

A salient image region is defined as an image part that is clearly different from its surround in terms of a number of attributes. In bottom-up processing, these attributes are defined as: contrast, color difference, brightness, and orientation. By measuring these attributes, visual saliency algorithms aim to predict the regions in an image that would attract our attention under free viewing co...

Abstract This paper describes an adaptive extraction of focus of attention region for saliency-based visual attention. The saliency map model generates the most salient and significant location in the visual scene. In human brain, there is an inhibition of return property for which current attending point is prevented from being attended again. Therefore, we need to pay attention to the focus o...

Saliency Detection is a hot research topic in both biological and computer vision. Salient structures, edges, regions would greatly contribute to high-level semantics understanding of people’s attention and improve retrieval precision, object detection, edge detection and etc. In this paper, based on the biological principle in visual system, we present a saliency detection system which combine...

Existing computational models of visual attention generally employ simple image features such as color, intensity or orientation to generate a saliency map which highlights the image parts that attract human attention. Interestingly, most of these models do not process any depth information and operate only on standard two-dimensional RGB images. On the other hand, depth processing through ster...

The notion of a saliency-based processing architecture [1] underlying human vision is central to a number of current theories of visual selective attention [e.g., 2]. On this view, focal-attention is guided by an overall-saliency map of the scene, which integrates (sums) signals from pre-attentive sensory feature-contrast computations (e.g., for color, motion, etc.). By linking the Posterior Co...

Saliency detection means detecting visually attractive regions in images. It is an aspect of exploring visual attention from a computer vision. Each image is segmented to get bags. Features are extracted from each bag. Features, including low-, mid-,and high-level, are incorporated into the learning and testing process. They are position, color, texture, scale, center prior, and boundary. From ...

Algorithms using “bag of features”-style video representations currently achieve state-of-the-art performance on action recognition tasks, such as the challenging Hollywood2 benchmark [1,2,3]. These algorithms are based on local spatiotemporal descriptors that can be extracted either sparsely (at interest points) or densely (on regular grids), with dense sampling typically leading to the best p...

The just noticeable distortion (JND) model plays an important role in measuring the visual visibility for spread transform dither modulation (STDM) watermarking. However, the existing JND model characterizes the suprathreshold distortions with an equal saliency level. Visual saliency (VS) has been widely studied by psychologists and computer scientists during the last decade, where the distorti...

References [1] Vikram T.N, Tscherepanow M. and Wrede B. A Visual Saliency Map based on Random Sub-Window Means. In proceedings of Iberian Conference on Pattern Recognition and Image Analysis, pp. 33-40 (2011). [2] Vikram T.N, Tscherepanow M. and Wrede B. A Random Center Surround Bottom up Visual Attention Model useful for Salient Region Detection. In IEEE Workshop on Applications of Computer Vi...