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An algorithm for autonomous selection of optimal landing site based on the image is proposed. Firstly, referenced rocks` shadow and light areas are extracted by the use of double threshold segmentation based on the two-dimensional maximum entropy. Then, the threshold segmentation image is processed further, including the combination of the shadow and light areas in order to form obstacle areas and...
Edge detection is an important task in image processing and becomes more complex for the colour image which provides more information in comparison to the gray image. In this paper it will be presented a colour edge detection approach based on the product of multiscale wavelet transform. The use of the product of multiscale transform improves the localization of detected edges comparing to the one...
This paper presents a novel method to find corners that are well located and stable interest points in a given image. Our corners are defined as intersection points of non collinear straight image edges, which are very robust against various image transformations like image scaling, rotation, translation and also to viewpoint and illumination changes. Some light updates on the linking edge step that...
We present a new method for the atlas-free brain segmentation of proton-density-like 3D MRI images. We show how steerable filters can be efficiently combined with parametric spline surfaces to produce a fast and robust 3D brain segmentation algorithm. The novelty lies in the computation of brain edge maps through optimal steerable surface detectors which provide efficient energies for the rapid optimization...
Distinctive features are crucial to many tasks in computer assisted minimally invasive surgeries (MIS). Most existing methods are difficult to extract distinctive features in MIS images. For better analysis of MIS images, we resort to blood vessels that are abundant and distinctive on the tissue surfaces. Based on vascular branching points, we propose a new type of vascular feature, branching segment...
In medical X-ray imaging, the detector intensity heavily influences the signal-to-noise ratio, and thus the image quality [1]. Consequently, image quality and patient dose are dependent on the performance of the Automatic Exposure Control. Introducing large opaque objects to the image, which can be considered disturbances for the dose control, leads to a loss of image quality (overexposed tissue)...
In this paper we propose a method to add scale-invariance to line descriptors for wide baseline matching purposes. While finding point correspondences among different views is a well-studied problem, there still remain difficult cases where it performs poorly, such as textureless scenes, ambiguities and extreme transformations. For these cases using line segment correspondences is a valuable addition...
We propose an interactive video segmentation system built on the basis of occlusion and long term spatio-temporal structure cues. User supervision is incorporated in a superpixel graph clustering framework that differs crucially from prior art in that it modifies the graph according to the output of an occlusion boundary detector. Working with long temporal intervals (up to 100 frames) enables our...
In this paper, we tackle the problem of road detection from RGB images. In particular, we follow a data-driven approach to segmenting the road pixels in an image. To this end, we introduce two road detection methods: A top-down approach that builds an image-level road prior based on the traffic pattern observed in an input image, and a bottom-up technique that estimates the probability that an image...
Object information is an important cue to discriminate between activities that draw part of their meaning from context. Most of current work either ignores this information or relies on specific object detectors. However, such object detectors require a significant amount of training data and complicate the transfer of the action recognition framework to novel domains with different objects and object-action...
According to the characteristics of Chinese characters image, we propose an improved corner detection method based on Harris algorithm and the ideal of FAST to improve detection rate for next feature extraction in this paper. First, the image of Chinese characters is detected for corners using Harris algorithm. Second, using the FAST for reference, the false corners are removed. The corners founded...
Automated tracking of cell populations' movement is vital for quantitative and systematic analysis of cell behaviors. However, it suffers from many challenges including complex cell morphology, undistinguished visual appearance, frequent occlusions, and irregular motion, etc. In this paper, we present a fully automatic and effective method to track hundreds of oval-shaped cells. A novel dual ellipsoidal...
Line segment is the most important feature for shape analysis and object recognition. In this study, a novel line detection method starting from endpoints is proposed. Firstly, the junctions and breakpoints are detected from the edge map. Then the connected edge pixels between any two junctions or breakpoints will be extracted, and taken as a line segment or a curve by using small eigenvalue analysis...
We present a model for video segmentation, applicable to RGB (and if available RGB-D) information that constructs multiple plausible partitions corresponding to the static and the moving objects in the scene: i) we generate multiple figure-ground segmentations, in each frame, parametrically, based on boundary and optical flow cues, then track, link and refine the salient segment chains corresponding...
In this paper we discuss the application of two-dimensional linear cellular automata (CA) rules with the help of fuzzy heuristic membership function to the problems of edge detection in image processing applications. We proposed an efficient and simple thresholding technique of edge detection based on fuzzy cellular automata transition rules optimized by Particle Swarm Optimization method (PSO). Finally,...
This paper discusses a method to extract character strings from scene images. In this method, the Canny edge detector is first applied to a scene image, and the binary edge image is then obtained. Next, small edge elements are separated from large edge elements because edge elements from characters are much smaller than edge elements from non-character objects such as signboards etc. However, many...
We propose two methods for detecting transparent text in images and recovering the background behind the text. Although text detection in natural scenes is an active research area, most current methods are focused on non-transparent text. To detect transparent text, we developed an adaptive edge detection method for edge-based text detection that can accurately detect text even under low contrast,...
Image segmentation is a fundamental task of image processing that consists in partitioning the image by grouping pixels into homogeneous regions. We propose a novel segmentation algorithm that consists in combining many runs of a simple and fast randomized segmentation algorithm. Our algorithm also yields a soft-edge closed contour detector. We describe the theoretical probabilistic framework and...
Gamma ray cameras can easily locate radiation hotspots where decontamination is required. Among them, the Compton camera that utilizes the Compton scattering is compact and lightweight because no radiation shielding is required. We have developed a Compton camera for quick visualization of the radioactive contamination. It features high detection efficiency by utilizing gamma ray detectors which is...
Several MRI-based attenuation correction methods have been reported for PET/MRI. The accuracy of the attenuation map (μ-map) from an MRI image depends on correctness of the segmentation of tissue and the attenuation coefficients to be assigned (μ-values). However, an MRI image does not reflect the attenuation of radiation and inaccurate assignment of μ-values affects the quantitative assessment of...
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