Grammatical Inference of Dashed Lines

Jonk, A.; Boomgaard, R. van den; Smeulders, A.W.M.

doi:10.1006/cviu.1999.0753

Cited by 5 publications

(2 citation statements)

References 13 publications

(13 reference statements)

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“…We proposed a scheme for both anisotropic convolution filtering and anisotropic recursive filtering. Convolution filtering is advantageous when considering locally steered filtering, as is the case in tracking applications [11,18,19]. Recursive filtering is more attractive when smoothing or differentiating the whole image array, for example in feature detection [3,15,20,21].…”

Section: Derivative Filtersmentioning

confidence: 99%

Fast Anisotropic Gauss Filtering

Geusebroek

Smeulders

Weijer

2002

Computer Vision — ECCV 2002

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We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction followed by a one dimensional filter in a non-orthogonal direction ϕ. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a computing perspective. An implementation scheme for normal convolution and for recursive filtering is proposed. Also directed derivative filters are demonstrated. For the recursive implementation, filtering an 512 × 512 image is performed within 65 msec, independent of the standard deviations and orientation of the filter. Accuracy of the filters is still reasonable when compared to truncation error or recursive approximation error. The anisotropic Gaussian filtering method allows fast calculation of edge and ridge maps, with high spatial and angular accuracy. For tracking applications, the normal anisotropic convolution scheme is more advantageous, with applications in the detection of dashed lines in engineering drawings. The recursive implementation is more attractive in feature detection applications, for instance in affine invariant edge and ridge detection in computer vision. The proposed computational filtering method enables the practical applicability of orientation scale-space analysis.

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Section: Derivative Filtersmentioning

confidence: 99%

Fast Anisotropic Gauss Filtering

Geusebroek

Smeulders

Weijer

2002

Computer Vision — ECCV 2002

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“…In the civil sector, the Steger's line detector has been used for the identification of roads from satellite images and for the study of traffic with the automatic recognition of lines of cars [11]. In physics, the Steger's algorithm has been used for recognizing gravitational waves from the study of time-frequency diagrams [12], and in document analysis to automate the process of digitizing lines in engineering drawings [13]. In machine vision, it has been highly exploited in 3D reconstruction techniques through stereo vision [14,15] and laser structured light techniques [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Automated Measurement of Geometric Features in Curvilinear Structures Exploiting Steger’s Algorithm

Giulietti

Chiariotti

Revel

2023

Sensors

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Accurately assessing the geometric features of curvilinear structures on images is of paramount importance in many vision-based measurement systems targeting technological fields such as quality control, defect analysis, biomedical, aerial, and satellite imaging. This paper aims at laying the basis for the development of fully automated vision-based measurement systems targeting the measurement of elements that can be treated as curvilinear structures in the resulting image, such as cracks in concrete elements. In particular, the goal is to overcome the limitation of exploiting the well-known Steger’s ridge detection algorithm in these applications because of the manual identification of the input parameters characterizing the algorithm, which are preventing its extensive use in the measurement field. This paper proposes an approach to make the selection phase of these input parameters fully automated. The metrological performance of the proposed approach is discussed. The method is demonstrated on both synthesized and experimental data.

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Graphics Recognition Techniques

Lladós¹,

Rusiñol²

2014

Handbook of Document Image Processing and Recognition

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Grammatical Inference of Dashed Lines

Cited by 5 publications

References 13 publications

Fast Anisotropic Gauss Filtering

Fast Anisotropic Gauss Filtering

Automated Measurement of Geometric Features in Curvilinear Structures Exploiting Steger’s Algorithm

Graphics Recognition Techniques

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