Fault-tolerant systems are such systems that can continue their operation, even in presence of faults. Redundancy as one of the main techniques in implementation of fault-tolerant control systems uses voting algorithms to choose the most appropriate value among multiple redundant and probably faulty results. Average (mean) voter is one of the commonest voting methods which is suitable for decis...

with quick development of digital images and the availability of imaging tools, massive amounts of images are created. therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. automatic image annotation (aia) or refers to attaching words, keywords or comments to an image or to a selected part of it. in this paper,...

Removing or filtering outliers and mislabeled instances prior to training a learning algorithm has been shown to increase classification accuracy. A popular approach for handling outliers and mislabeled instances is to remove any instance that is misclassified by a learning algorithm. However, an examination of which learning algorithms to use for filtering as well as their effects on multiple ...

For multi atlas-based segmentation approaches, a segmentation fusion scheme which considers local performance measures may be more accurate than a method which uses a global performance measure. We improve upon an existing segmentation fusion method called SIMPLE and extend it to be localized and suitable for multi-labeled segmentations. We demonstrate the algorithm performance on 23 CT scans o...

This paper describes a new Hough transform (HT) algorithm for multi-objective detection. The core principle of HT—voting principle, which needs to find the maximal voting rate, makes HT impossible to detect many targets from single image synchronously. An improved HT algorithm based on clustering is presented. When the number of targets in the image is known, all of targets can be detected once...

A mobility aid for the visually impaired should be able to detect and warn about nearby obstacles. Reliable detection of curbs and steps is critical to meet this goal. This paper describes a stereo-vision based algorithm that estimates the underlying planar geometry of the 3D scene to generate hypotheses for the presence of steps. Tensor voting is used to calculate globally consistent normals a...

This paper presents a novel image thresholding algorithm, termed as random spatial sampling and majority voting based image thresholding algorithm (RMIT). RMIT firstly obtains a population of binary subimages by using random spatial sampling and Otsu’s thresholding algorithm [1]. Then RMIT aggregates these binary subimages into a consensus binary image by majority voting technique. Since the su...