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Detection of Object Edges in Aerospatial Cartographic Images

Degtyarev S. V., Miroshnichenko S. Yu., Titov V. S.

Machine Graphics and Vision

2009

Vol. 18, No. 4

427-437

Modern geographic information systems (GIS) have a wide range of applications, including town-planning, town traffic control, ecology, logistics and others. These GIS require frequent update's using information supplied by aerospatial cartographic images. The standard approach to processing aerospatial cartographic images is interactive vectorization using software tools. This paper presents a method for object edge detection which is part of automated vectorization of aerospatial cartographic images. The method uses edge detection with local scale estimation and is well suited for locating anthropogenic objects (such as buildings and roads). The effectiveness of the proposed method has been experimentally verified on real aerospatial cartographic images.

The calibration method for stereoscopic vision system

Titov V. S., Degtyarev S. V., Truphanov M. I.

Machine Graphics and Vision

2008

Vol. 17, No. 4

373-387

Stereoscopic vision systems are used not only in visual design computing but also in many other applications. In stereoscopic vision, an important property is the accuracy of three-dimensional reconstruction. This property depends considerably on the quality of the vision system calibration. The known solutions to the calibration problem are based on determining calibration parameters from an image of a special pattern. Our method allows calibration of the stereoscopic vision without such a special pattern. The calibration includes the following basic stages: selection of an object used in the calibration (one a priori unknown object instead of a special model object) which is chosen from a set of objects existing in a working scene, calibration of the angles between two cameras which are part of the stereoscopic vision system, and calibration of the distances between two cameras. The calibration parameters are calculated with the aid of images of calibration objects. This approach allows us to perform an adaptive calibration of the vision system (automatic calibration is performed from time to time when necessary) because this process does not require placing of the special calibration object in the working scene, it does not interrupt execution of main function of the vision system and increases the calibration accuracy since possible errors which may be introduced during the placement of the calibration object do not affect the result of the calibration.