13,245 research outputs found

    An Improved Algorithm for Eye Corner Detection

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    In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented. The algorithm is a modification of the Santos and Proenka Method. In the first step, we detect the face and the eyes using classifiers based on Haar-like features. We then segment out the sclera, from the detected eye region. From the segmented sclera, we segment out an approximate eyelid contour. Eye corner candidates are obtained using Harris and Stephens corner detector. We introduce a post-pruning of the Eye corner candidates to locate the eye corners, finally. The algorithm has been tested on Yale, JAFFE databases as well as our created database

    GeoSay: A Geometric Saliency for Extracting Buildings in Remote Sensing Images

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    Automatic extraction of buildings in remote sensing images is an important but challenging task and finds many applications in different fields such as urban planning, navigation and so on. This paper addresses the problem of buildings extraction in very high-spatial-resolution (VHSR) remote sensing (RS) images, whose spatial resolution is often up to half meters and provides rich information about buildings. Based on the observation that buildings in VHSR-RS images are always more distinguishable in geometry than in texture or spectral domain, this paper proposes a geometric building index (GBI) for accurate building extraction, by computing the geometric saliency from VHSR-RS images. More precisely, given an image, the geometric saliency is derived from a mid-level geometric representations based on meaningful junctions that can locally describe geometrical structures of images. The resulting GBI is finally measured by integrating the derived geometric saliency of buildings. Experiments on three public and commonly used datasets demonstrate that the proposed GBI achieves the state-of-the-art performance and shows impressive generalization capability. Additionally, GBI preserves both the exact position and accurate shape of single buildings compared to existing methods

    Cardiac Cavity Segmentation in Echocardiography Using Triangle Equation

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    In this paper, cardiac cavity segmentation in echocardiography is proposed. The method uses triangle equation algorithms to detect and reconstruct the border. Prior to the application of both algorithms, some preprocessings have to be carried out. The first step is high boost filter to enhance high frequency component while still keeping the low frequency component. The second step is applying morphological and thresholding operations to eliminate noise and convert the image into binary image. The third step is negative laplacian filter to apply edge detector. The fourth step is region filter to eliminate small region. The last step is using triangle equation to detect and reconstruct the imprecise border. This technique is able to perform segmentation and detect border of cardiac cavity from echocardiographics sequences. Keywords: cardiac cavity, high boost filter, morphology, negative laplacian, region filter, and triangle equation

    A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor

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    In this paper we present a new methodology for edge detection in digital images. The first originality of the proposed method is to consider image content as a parametric surface. Then, an original parametric local model of this surface representing image content is proposed. The few parameters involved in the proposed model are shown to be very sensitive to discontinuities in surface which correspond to edges in image content. This naturally leads to the design of an efficient edge detector. Moreover, a thorough analysis of the proposed model also allows us to explain how these parameters can be used to obtain edge descriptors such as orientations and curvatures. In practice, the proposed methodology offers two main advantages. First, it has high customization possibilities in order to be adjusted to a wide range of different problems, from coarse to fine scale edge detection. Second, it is very robust to blurring process and additive noise. Numerical results are presented to emphasis these properties and to confirm efficiency of the proposed method through a comparative study with other edge detectors.Comment: 21 pages, 13 figures and 2 table

    Broadband X-ray Imaging and Spectroscopy of the Crab Nebula and Pulsar with NuSTAR

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    We present broadband (3 -- 78 keV) NuSTAR X-ray imaging and spectroscopy of the Crab nebula and pulsar. We show that while the phase-averaged and spatially integrated nebula + pulsar spectrum is a power-law in this energy band, spatially resolved spectroscopy of the nebula finds a break at ∌\sim9 keV in the spectral photon index of the torus structure with a steepening characterized by ΔΓ∌0.25\Delta\Gamma\sim0.25. We also confirm a previously reported steepening in the pulsed spectrum, and quantify it with a broken power-law with break energy at ∌\sim12 keV and ΔΓ∌0.27\Delta\Gamma\sim0.27. We present spectral maps of the inner 100\as\ of the remnant and measure the size of the nebula as a function of energy in seven bands. These results find that the rate of shrinkage with energy of the torus size can be fitted by a power-law with an index of Îł=0.094±0.018\gamma = 0.094\pm 0.018, consistent with the predictions of Kennel and Coroniti (1984). The change in size is more rapid in the NW direction, coinciding with the counter-jet where we find the index to be a factor of two larger. NuSTAR observed the Crab during the latter part of a Îł\gamma-ray flare, but found no increase in flux in the 3 - 78 keV energy band
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