Image Shape Extraction using Interval Methods
نویسنده
چکیده
This paper proposes a new method for recognition of geometrical shapes (such as lines, circles or ellipsoids) in an image. The main idea is to transform the problem into a bounded error estimation problem and then to use an interval-based method which is robust with respect to outliers. The approach is illustrated on an image taken by an underwater robot where a spheric buoy has to be detected. The results will then be compared to those obtained by the more classical generalized Hough transform.
منابع مشابه
Reduced-Reference Image Quality Assessment based on saliency region extraction
In this paper, a novel saliency theory based RR-IQA metric is introduced. As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. In order to extract the salient regions, we use blob decomposition (BD) tool as a texture component descriptor. A new method for blob decomposition is propos...
متن کاملTuning Shape Parameter of Radial Basis Functions in Zooming Images using Genetic Algorithm
Image zooming is one of the current issues of image processing where maintaining the quality and structure of the zoomed image is important. To zoom an image, it is necessary that the extra pixels be placed in the data of the image. Adding the data to the image must be consistent with the texture in the image and not to create artificial blocks. In this study, the required pixels are estimated ...
متن کاملStatistical Shape and Appearance Models for Segmentation and Classification
In this dissertation we develop and apply models of shape and models of image intensities (appearance models) in object-based image processing tasks. We make contributions in three areas of interest: constructing novel flexible models of shape and of image intensities, using these models to extract object boundaries from images, and analyzing differences between groups of shapes from given, ext...
متن کاملImage object extraction with shape and edge-driven Markov random field model
For object extraction, the target object in images often cannot be extracted completely and accurately using only low-level image features, especially from cluttered, occluded and noisy images. In practice, the shape of the target object is often known in advance, and edges can be extracted directly from image, which can contribute to the object extraction task. The authors introduce shape prio...
متن کاملParameterizing Arbitrary Shapes via Fourier Descriptors for Evidence-Gathering Extraction
According to the formulation of the Hough Transform, it is possible to extract any shape that can be represented by an analytic equation with a number of free parameters. Nevertheless, the extraction of arbitrary shapes has centered on nonanalytic representations based on a table which specifies the position of edge points relative to a fixed reference point. In this paper we develop a novel ap...
متن کامل