Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development, more comprehensive information, such as depth cue, inter-image correspondence, or temporal relationship, is available to extend image saliency detection to RGBD saliency detection, co-saliency detection, or video sal...

In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent, surprised and disgusted faces was found both under upri...

In this paper, a novel method is presented for detection and classification of the faultyphase/region in the stator winding of synchronous generators on the basis of the resulting harmoniccomponents that appear in the terminal voltage waveforms. Analytical results obtained through DecisionTree (DT) show that the internal faults are not only detectable but also they can be classified andthe rela...

Top-down saliency models produce a probability map that peaks at target locations specified by a task/goal such as object detection. They are usually trained in a fully supervised setting involving pixel-level annotations of objects. We propose a weakly supervised top-down saliency framework using only binary labels that indicate the presence/absence of an object in an image. First, the probabi...

Automatic image segmentation is emerging field in image processing research domain. Many researchers have developed various techniques for segmenting the interested region in an image. Saliency based image segmentation is one of the keen area of research. In a visual scene, the objects which are different from their surroundings get more visual importance and get high gaze attention of the view...

Ability of human visual system to detect prominent regions in an image is fast, reliable and efficient. Computational modeling of this extraordinary behavior is termed as saliency detection. Saliency detection identifies salient regions in an image and is relevant in many computer vision applications such as object recognition, image segmentation, image retrieval etc. The term co-saliency can b...

Authentication time is the main and important part of the authentication system. Normally the response time should be fast but as the number of persons in the database increases, there is probability of more response time taken for authentication. The need of fast authentication system arises so that authentication time (matching time) is very less. This paper proposes a sliding window approach...

Harris corner detection algorithm called Harris corner detector is a very effective corner algorithm for gray-scale images. The corners extracted by Harris corner detector are stable, reliable, homogeneous and reasonable. However, it has own inevitable limitations. For the shape recognition of parts, an improved Harris corner detector is proposed in this paper. Based on the analysis of Harris c...

Co-saliency detection is a newly emerging and rapidly growing research area in computer vision community. As a novel branch of visual saliency, co-saliency detection refers to the discovery of common and salient foregrounds from two or more relevant images, and can be widely used in many computer vision tasks. The existing co-saliency detection algorithms mainly consist of three components: ext...

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...