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Co-saliency detection aims at discovering the common and salient objects in multiple images. It explores not only intra-image but extra inter-image visual cues, and hence compensates the shortages in single-image saliency detection. The performance of co-saliency detection substantially relies on the explored visual cues. However, the optimal cues typically vary from region to region. To address this...
Graph-based segmentation is gaining popularity among the many approaches in performing image segmentation, primarily due to its ability in reflecting global image properties. The most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. We developed a unified framework for volumetric...
Image fusion is the process of merging all similar information from two or more images into a single image. The aim is to provide an image fusion method for fusing the images from the different modalities so that the fusion image will give more information without losing input information and also without any redundancy. This paper gives the efficient method for fusion purpose, by fusing LIDAR and...
The effective application of spatio-temporal network models to neuroimaging data is an emerging challenge in the field of neuroscience, and could help scientists to better understand the behavior of the brain across a range of different experiments. One of the main problems with deriving spatiotemporal networks is that it is difficulty to provide a clear view of computed results. In this paper, we...
The blind can only get perceptive and audio information. Mobile devices could provide the blind great help. This project deals with a new android-based blind reader system designed for the blind to get photocopy information. However, it is difficult for the blind to locate and select items visualized using touchscreen. So this paper presents non-visual interaction which combines auditory interface...
The attractive structures in human perception often correspond to objects of interest and have great practical importance. Therefore, extracting the attractive structures from images is a fundamental problem in many image analysis tasks. We in this letter propose a novel nonuniform method to maintain the attractive structures for image analysis while removing meaningless details. Our nonuniform method...
With the aim of inspecting ground pipelines autonomously, an Unmanned Aerial Vehicle (UAV) will be used in this research. Arbitrary object contours in a 2D image could be considered as plane shapes, which will be used to identify their structures. Vision-based tracking is proposed because it is relatively more direct and more accurate than other sensors such as GPS. Image processing is applied to...
Infrared and visible image fusion can integrate the target information of an infrared image and the spatial detail of a visible image to constitute a fused image, which has more complete and accurate description of the same scene than a single image. In this paper, a novel image fusion method using saliency detection based on non-subsampled shearlet transform (NSST) is proposed for infrared and visible...
X-ray angiography is a common method for image-guided navigation comprising surgical devices and vessel contours detection which can offer visual feedback to physicians. However, for the sake of both physicians' and patients' health, the contrast agent is injected intermittently and in a low dosage, so the X-ray images are not always of adequate quality for visual examination. So the navigation, which...
Initial results on a fast approach for detecting straight line segments based on the combination of local search and Hough Transform (HT) is discussed in this paper. Though HT is a robust method for extracting patterns from noisy images, it does not regard the level of occlusions and the minimum allowable line segment length. We propose a Sliding Window (SW) concept which eliminates most of the spurious...
Pose estimation and 3D environment reconstruction are crucial for autonomous navigation in mobile robotics. Robust dense visual odometry based on a RGB-D sensor uses all pixels to estimate frame-to-frame motion by minimizing the photometric and geometric error. 3D coordinates of each pixel are calculated necessarily with its corresponding depth. However, depths of some pixels near object boundaries...
In this work, two enhancement methods are proposed to speed up junction detection performed by the JUDOCA detector. The first enhancement method minimizes the number of junction candidates on which the circular kernel is applied. This is achieved by introducing a suppression technique that takes both the thin and thick edge images into consideration. The second method works on relaxing the step of...
Exhaustive scanning is a popular scheme for the detection of visual objects in images. In this paper, we propose a polyline-driven detection scheme with an application to stop sign detection. Given an input image, we first extract basic polylines, including line segments and 2-piece polylines, from its edge image. Line segments are then used to generate a set of hypothesis boxes, i.e., a space of...
Region-based Image Retrieval (RBIR), which bases itself on image segmentation rather than global features or key-point-based local features, is a branch of Content-based Image Retrieval. This paper proposes a novel RBIR-oriented image segmentation algorithm named Edge Integrated Minimum Spanning Tree (EI-MST). The difference between EI-MST and the traditional MST-based methods is that EI-MST generates...
Recently LiDAR-camera systems have rapidly emerged in many applications. The integration of laser range-finding technologies into existing vision systems enables a more comprehensive understanding of 3D structure of the environment. The advantage, however, relies on a good geometrical calibration between the LiDAR and the image sensors. In this paper we consider visual odometry, a discipline in computer...
For a robot to operate efficiently in a human centered environment, it should be able to interact and learn unknown objects autonomously. Such capabilities will enable a robot to enrich its internal knowledge of the environment without human assistance. However, a crucial limitation of robots is their inability to comprehend representations of novel objects without priors. Human efforts are required...
We present the design and implementation of an automated event summarization system that leverages publicly available data from online sources. A novel Network of Networks (NoN) model is proposed to represent a multimodal data set comprising microblog posts, news articles, and images that describe current attitudes, trends, and events being shared by individuals and organizations. In this model, networks...
Diffusion-based salient region detection has recently received intense research attention. In this paper, we propose a salient region detection method based on the foreground and background propagation with manifold ranking. By considering the spatial variance of superpixel clusters, foreground and background seed regions are extracted preliminarily. Then, in order to produce a pixel-accurate saliency...
Just noticeable difference (JND), which reveals the visibility of our human visual system (HVS), is useful for image/video coding. Due to the content complexity, it is hard to accurately estimate the JND thresholds for different image blocks (e.g., edge and texture). Research on cognitive science indicates that the HVS is adaptive to extract the visual regularities for scene perception and understanding...
Bag of visual words (BoVW) remains a very competitive representation in the domain of scene classification. In this framework, extracting SIFT descriptors on a dense grid of pixels has shown to lead to a better performance. However, due to the nature of SIFT as an edge-based descriptor, computing SIFT on homogeneous regions might result in non-stable region descriptors. The suggested solution in the...
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