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In this paper, we present an efficient edge chain detection algorithm by applying the Helmholtz principle on the gradient magnitude map of an image. An edge chain validation method is proposed which uses the “relative number of false alarms” (RNFA) instead of the traditional “number of false alarms” (NFA). The edge chains are detected first and then validated according to their RNFA values. In this...
In this paper, we present a novel method for seamlessly mosaicking panoramic images based on superpixels in the graph cuts energy minimization framework. To effectively ensure that all seamlines are detected in the laterally continuous regions with the high image similarity and the low object dislocation, the energy functions adopted in graph cuts combine the pixel-level similarities of image characteristics,...
This paper presents an method that matches points and line segments jointly on wide-baseline stereo images. In both two images to be matched, line segments are extracted and those spatially adjacent ones are intersected to generate V-junctions. To match V-junctions from the two images, we extract for each of them an affine and scale invariant local region and describe it with SIFT. The putative V-junction...
As the vital procedure for exploiting line segments extracted from images for solving computer vision problems, Line Segment Matching (LSM) has received growing attentions from researcher in recent years, and a considerable number of methods have been proposed. However, no one has attempted to solve two major problems in this area. The first is how to evaluate different methods in an unbiased way...
Superpixels are an oversegmentation of an image and popularly used as a preprocessing in many computer vision applications. Many state-of-the-art superpixel segmentation algorithms rely either on minimizing special energy functions or on clustering pixels in the effective distance space. While in this paper, we introduce a novel algorithm to produce superpixels based on the edge map by utilizing a...
In this paper, we propose a novel line segment detector, named as NETLines, which can produce a set of accurate line segments and a set of node-connected line-networks formed by connection of the line segments and the image boundary. Based on the line segments generated by other line segment detectors (e.g., EDLines [1]) on an edge map, the proposed algorithm efficiently makes use of the gradient...
In this paper we propose an approach to holistic scene understanding that reasons jointly about regions, location, class and spatial extent of objects, presence of a class in the image, as well as the scene type. Learning and inference in our model are efficient as we reason at the segment level, and introduce auxiliary variables that allow us to decompose the inherent high-order potentials into pairwise...
A hierarchical shadow detection algorithm for color aerial images is presented in this paper to meet two challenges for static shadow detection in the literature: different brightness and illumination conditions in different images and the complexity of aerial images. The hierarchical algorithm consists of two levels of processing: the pixel level classification, achieved through modelling an image...
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