Template-Free Wavelet-Based Detection of Local Symmetries

Püspöki, Zsuzsanna; Unser, Michaël

doi:10.1109/tip.2015.2436343

Cited by 13 publications

(10 citation statements)

References 27 publications

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“…The illustration of circular harmonics for order three is presented in Figure 8 (i.). An application of circular harmonic wavelets on local symmetry detection is presented in (Püspöki and Unser, 2015).…”

Section: Steerable Waveletsmentioning

confidence: 99%

Transforms and Operators for Directional Bioimage Analysis: A Survey

Püspöki

Storath

Sage

et al. 2016

Advances in Anatomy, Embryology and Cell Biology

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417

296

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We give a methodology-oriented perspective on directional image analysis and rotation-invariant processing. We review the state of the art in the field and make connections with recent mathematical developments in functional analysis and wavelet theory. We unify our perspective within a common framework using operators. The intent is to provide image-processing methods that can be deployed in algorithms that analyze biomedical images with improved rotation invariance and high directional sensitivity. We start our survey with classical methods such as directional-gradient and the structure tensor. Then, we discuss how these methods can be improved with respect to robustness, invariance to geometric transformations (with a particular interest in scaling), and computation cost. To address robustness against noise, we move forward to higher degrees of directional selectivity and discuss Hessian-based detection schemes. To present multiscale approaches, we explain the differences between Fourier filters, directional wavelets, curvelets, and shearlets. To reduce the computational cost, we address the problem of matching directional patterns by proposing steerable filters, where one might perform arbitrary rotations and optimizations without discretizing the orientation. We define the property of steerability and give an introduction to the design of steerable filters. We cover the spectrum from simple steerable filters through pyramid schemes up to steerable wavelets. We also present illustrations on the design of steerable wavelets and their application to pattern recognition.

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Section: Steerable Waveletsmentioning

confidence: 99%

Transforms and Operators for Directional Bioimage Analysis: A Survey

Püspöki

Storath

Sage

et al. 2016

Advances in Anatomy, Embryology and Cell Biology

Self Cite

417

296

View full text Add to dashboard Cite

show abstract

“…Detecting junction structure in images has been studied for years [24,26,27,31,32,33,34]. In the early stage, junction was studied as corner points [31,32].…”

Section: Junction Detectionmentioning

confidence: 99%

“…In this experiment, the junctions are detected by ACJ firstly in original image I and scaled image s(I) with the factor s firstly. Then we find the corresponding ACJ in the image pair by using the inequalities (26) and (24) while ignoring the inequality (25). For the sake of comparing the scale of junctions with respect to factor s, all the correspondences are shown with colored circle.…”

Section: Comparison With Acjmentioning

confidence: 99%

“…Ideally, the information contained by a pair of junctions enables us to recover the correspondences between images up to affine transformations. However, due to the difficulties in the estimation of the endpoints of junction branches, most of junction detection algorithms [23,24,25,26,27,28] concentrate on identifying the locations and orientation of branches while ignoring their length. This actually simplifies junctions as key-points and does not fully exploit their capabilities for image correspondences.…”

Section: Introductionmentioning

confidence: 99%

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Anisotropic-Scale Junction Detection and Matching for Indoor Images

Xue

Xia

Bai

et al. 2018

IEEE Trans. on Image Process.

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Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales which however contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction, and are thus named as anisotropicscale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g. key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.

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“…Zheng et al [17] used two convolutional templates and triangular part detectors that were combined to calculate point coordinates. Püspöki and Unser [18] proposed an improved filtering method to acquire exact coordinates. The algorithm has a faster calculation speed and better real-time performance.…”

Section: Introductionmentioning

confidence: 99%

High-Precision Calibration of Omnidirectional Camera Using an Iterative Method

Gong

et al. 2019

IEEE Access

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A distorted checkerboard image affects the precision of omnidirectional camera calibration because of the inaccurate localization of the feature points. To solve this problem, an iterative refinement method is presented. First, the initial parameters are obtained using the traditional calibration method, and the distorted checkerboard is transformed to a distortion-free plane by the projection model that is estimated by initial parameters. Then, the feature point coordinates of the corrected image are extracted. The calibration parameters are recomputed using the refinement of new point locations until the camera parameters converge. This iterative refinement method improves the localization accuracy of feature points and, consequently, of camera calibration. The correctness and effectiveness of the method are verified by a series of simulations and physical experiments. The experiments show that the reprojection errors of feature points are reduced by 39% compared to traditional methods.INDEX TERMS Omnidirectional camera calibration, feature point extraction.

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Template-Free Wavelet-Based Detection of Local Symmetries

Cited by 13 publications

References 27 publications

Transforms and Operators for Directional Bioimage Analysis: A Survey

Transforms and Operators for Directional Bioimage Analysis: A Survey

Anisotropic-Scale Junction Detection and Matching for Indoor Images

High-Precision Calibration of Omnidirectional Camera Using an Iterative Method

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