Quality-aware deformable models for change detection

Agouris, Peggy; Gyftakis, S.; Stefanidis, Anthony

doi:10.1109/icip.2001.958616

Cited by 7 publications

(6 citation statements)

References 2 publications

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“…The method is sensitive to the geometry of features and uses set operations such as union, intersection, complementation, dilation, erosion and thinning to identify geometrical characteristics of objects (Zhang et al., 1999; Amini et al., 2002a). Snakes , in conjunction with dynamic programming , are used for extraction of cultural structures such as roads and buildings (Agouris et al., 2001a, b; Péteri et al., 2004). Dynamic programming provides an optimised solution to road modelling (Gruen and Li, 1995).…”

Section: Introductionmentioning

confidence: 99%

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Road extraction based on fuzzy logic and mathematical morphology from pan‐sharpened ikonos images

Mohammadzadeh

Tavakoli

Zoej

2006

The Photogrammetric Record

109

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Automatic extraction of geospatial features has been the subject of extensive research in the past three decades. Here, an approach based on fuzzy logic and mathematical morphology is proposed, to extract main road centrelines from pan‐sharpened IKONOS images. In the IKONOS images, a standard deviation of 10 grey levels has been measured for the road classes. In the proposed fuzzy logic system, just one arbitrary pixel (up to a maximum of 3 pixels) provides an adequate initial value. Road identification requires neither the numbers of the classes nor the corresponding mean values; then, using advanced morphological concepts, the road centreline is extracted. The method is applied to pan‐sharpened IKONOS images of urban, suburban and rural areas around the Pyramids in Egypt, and Rasht City and Kish Island in Iran. The extracted road centrelines have an average error of 0·504 pixel and root mean square error of 0·036 pixel. The method is more accurate at road intersections and on curves than on straight sections of road. The extracted road is then used as a direct input to a geographical information system (GIS).

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Section: Introductionmentioning

confidence: 99%

“…Snakes , in conjunction with dynamic programming , are used for extraction of cultural structures such as roads and buildings (Agouris et al., 2001a, b; Péteri et al., 2004). Dynamic programming provides an optimised solution to road modelling (Gruen and Li, 1995).…”

Section: Introductionmentioning

confidence: 99%

Road extraction based on fuzzy logic and mathematical morphology from pan‐sharpened ikonos images

Mohammadzadeh

Tavakoli

Zoej

2006

The Photogrammetric Record

109

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“…대용량의 도로관련 수치지도의 효율적인 갱신을 위하여 최 신의 항공사진이나 위성영상에서 도로망을 추출하여 변화 를 탐지하거나 구축시기가 상이한 이종의 공간정보를 이용하 여 변화를 탐지하고 갱신하는 연구가 꾸준히 진행되고 있다 (Agouris et al, 2001a;Agouris et al, 2001b;Beyen et al, 2012;Eidenbenz et al, 2000;Fortier et al, 2001;Yang et al, 2000;Zhang and Baltsavias, 2002;Zhang and Couloigner, 2005). 특히 벡터 자료구조의 수치지도 간 변화탐지를 위한 연 구에서는 이종의 공간정보간의 매칭 기법을 기반으로 두 지도 간의 모든 객체를 비교하여 변화를 탐지하는 방법이 적용되 고 있다 (Badard, 1999;Gabay and Doytsher, 1994;Goesseln and Sester, 2003;Uitermark et al, 1999;Saalfeld, 1988;Sui et al, 2004;Walter andFritsch, 1999, Xiong andSperling, 2004;Zhang et al, 2010).…”

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Automatic Change Detection Based on Areal Feature Matching in Different Network Data-sets

Kim¹,

Huh²,

Yu³

et al. 2013

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fréchet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fréchet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

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“…This initial contour can then he used as an approximation to automatically extract the next object instance. This differential snakes technique has been demonstrated to function very well in cases where the object monitoring rate is high, thus ensuring relatively small variations between successive instances [4]. The result of differential snakes is the automated identification of the closed polygons that represent the object's outlines at different instances.…”

Section: Differential Snakes For Tracking Objects With Closed Curvesmentioning

confidence: 99%

“…At the core of our approach is the extension of the differential snakes method as they were introduced in [4]. The authors in [4] make use of prior information for an object (an older record of the shape of the object) and accompanying accuracy estimates to detect automatically changes in the object's outline, and update the corresponding CIS database (shape and corresponding accuracy). In this paper we enhance this model to identify object translation, rotation, and/or deformation from local outline variations, and to support the tracking of closed-outline areal objects.…”

Section: Introductionmentioning

confidence: 99%

Tracking deformable objects in geospatial applications

Gyftakis

Agouris

Stefanidis

2004 International Conference on Image Processing, 2004. ICIP '04.

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I n this paper we describe a novel upprouch f b r change detection of moving defrmable ohjects. We o.wiime that each object is represented us a closedpolygon (conver or concave). First, we use di,@entiul snakes Io track the object oirtline between two different frames. Next. we examine the geometric properties (area moments, and principal axes) of these hvo polvgons and we estimate their c~hunges (translation, rotation, area erpanded or contracted). Additionally, using rcm1t.s from invariunt moments theory we compute a similarity index among di@erent instances of an ohject ' . s histo?. This infirmution is used to npdute geospatial datuhases und to siippart comp1e.r analysis. Experimental results on real imagery illiistrulr the capuhilities of o w approach.

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Quality-aware deformable models for change detection

Cited by 7 publications

References 2 publications

Road extraction based on fuzzy logic and mathematical morphology from pan‐sharpened ikonos images

Road extraction based on fuzzy logic and mathematical morphology from pan‐sharpened ikonos images

Automatic Change Detection Based on Areal Feature Matching in Different Network Data-sets

Tracking deformable objects in geospatial applications

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