Real-Time Imaging 10 (2004) 103–116 Real time contour tracking with a new edge detector V. Gemignani a, *, M. Paterni a , A. Benassi a ,M.Demi a,b a CNR Institute of Clinical Physiology, Via Moruzzi, 1 Pisa 56124, Italy b Esaote SpA, Florence, Italy Abstract Inthispaper,anewsystemforrealtimecontourtrackingispresented.Ifaroughcontourofthedesiredstructureisavailableon thefirstimageofasequence,thesystemcanautomaticallyoutlinethecontoursonthesubsequentimagesatvideorate.Themethod we used is based on a new edge detector which was obtained by the generalization of the first order absolute central moment operator.Thenewalgorithmprovedtobeveryrobusttonoiseandfastenoughtobeimplementedinrealtime.Thecontourtracking procedurewasimplementedonanintegratedsoftware/hardwareplatformcomposedofapersonalcomputerequippedwithadigital signalprocessingboard.Thesystemcancaptureananalogvideosignalwitharesolutionof512  512pixels,25frames/s,processthe dataanddisplaytheresultsinrealtime.Agraphicaluserinterfaceisalsoavailabletointeractwiththesystem.Testsonimagesofthe descending thoracic aorta and of a carotid, recorded by echocardiography, are reported. The cross-sectional area of the aorta and thediameterofthecarotidwerecomputedinrealtimeandplottedontheuserinterface.Thesystemprovedtobeausefultoolfor the investigation of vascular mechanisms. r 2004 Elsevier Ltd. All rights reserved. 1. Introduction Contour tracking on sequences of images is much debated in image analysis. The topic is of particular relevance in various application areas, such as robotics, video surveillance, video conferencing, human–compu- terinteractionandmedicalimaging [1–7].Ingeneral,the goal is to track the silhouette of a moving object throughoutasequenceofimages.Severalpapersexploit a contour tracking technique to approach the problem of object tracking, focusing their attention on the position of the object rather than on its shape. People and car tracking systems [1,2], whose purpose is to locatethepositionofoneormoremovingobjectsinside a scene, are typical examples. Such papers are usually notpreoccupiedwiththeexactdetectionofthecontour. Onthecontrary,otherapplicationsfocusonanaccurate definitionoftheshapeoftheobjectunderinvestigation. Examples can be found in medical imaging, where the silhouette of an anatomical structure provides informationofclinicalinterest [3–5].Isnotaneasytask to track the contour of an object automatically. The complexity of the problem remarkably increases when the object is not rigid, the movement is three-dimen- sional(3D),thebackgroundoftheimageiscomplexor theviewoftheobjectispartiallyoccluded [6,7].Further difficulties arise when real time performances are required. Despite the large amount of literature, a general solution to the problem of contour tracking does not exist, so the issue is still an open problem. In recent years, methods based on the active contours have often been used to track the contours of structures under investigation in image sequences [8]. These methods usually require the minimization of an energy function associatedtoadeformablecontinuouscurve.Ingeneral, two energy terms are considered: (i) an internal energy, which increases when the deformation of the curve increases and (ii) an external energy, which increases when the distance between the curve and the contour points increases. A starting curve which approximates thecontourisgivenandthefinalcurveisacompromise between contour smoothness and closeness to the data. As regards the external energy, the magnitude of the gradientofGaussian(GoG)iscommonlyusedtoweigh the distance between the curve and the contour points. One of the advantages of using an approach based on the active contours is the reduction of the amount of data that must be processed, which is limited to a neighborhood of the starting curve. Nevertheless, when ARTICLE IN PRESS *Corresponding author. Tel.: +39-050-3152612; fax: +39-050- 3152166. E-mail address: gemi@ifc.cnr.it (V. Gemignani). 1077-2014/$-see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.rti.2004.02.005