Edge detection: a review of dissimilarity evaluations and a proposed normalized measure

Magnier, Baptiste

doi:10.1007/s11042-017-5127-6

Cited by 22 publications

(47 citation statements)

References 52 publications

(67 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…, k = 2 for [21,22] Symmetric distance [3,5] [29] Γ(G t , D c ) = FP+FN |Gt| 2 · ∑ p∈Dc d 2 Gt (p) None Complete distance measure [6] Ψ(G t , D c ) = FP+FN |Gt| 2 · ∑…”

Section: Appendix Amentioning

confidence: 99%

Shape Similarity Measurement for Known-Object Localization: A New Normalized Assessment

Magnier

Moradi

2019

J. Imaging

Self Cite

View full text Add to dashboard Cite

This paper presents a new, normalized measure for assessing a contour-based object pose. Regarding binary images, the algorithm enables supervised assessment of known-object recognition and localization. A performance measure is computed to quantify differences between a reference edge map and a candidate image. Normalization is appropriate for interpreting the result of the pose assessment. Furthermore, the new measure is well motivated by highlighting the limitations of existing metrics to the main shape variations (translation, rotation, and scaling), by showing how the proposed measure is more robust to them. Indeed, this measure can determine to what extent an object shape differs from a desired position. In comparison with 6 other approaches, experiments performed on real images at different sizes/scales demonstrate the suitability of the new method for object-pose or shape-matching estimation.

show abstract

“…, k = 2 for [21,22] Symmetric distance [3,5] [29] Γ(G t , D c ) = FP+FN |Gt| 2 · ∑ p∈Dc d 2 Gt (p) None Complete distance measure [6] Ψ(G t , D c ) = FP+FN |Gt| 2 · ∑…”

Section: Appendix Amentioning

confidence: 99%

Shape Similarity Measurement for Known-Object Localization: A New Normalized Assessment

Magnier

Moradi

2019

J. Imaging

Self Cite

View full text Add to dashboard Cite

show abstract

“…Various evaluation methods have been proposed in the literature to assess different shapes of edges using pixel-based ground truth (see reviews in [1], [2], [3], [4]). Indeed, a supervised evaluation criterion computes a dissimilarity measure be-tween a ground truth (G t ) and a detected contour map (D c ) of an original image I.…”

Section: On Existing Normalized Measuresmentioning

confidence: 99%

“…Various edge detection evaluations involving confusion matrices have been developed , cf. [3] [4]. The Dice measure [10] is one well known example:…”

Section: On Existing Normalized Measuresmentioning

confidence: 99%

“…This type of assessment is useful for region segmentation evaluation [10], but, a reference-based edge map quality measure requires that a displaced edge should be penalized in function of FPs and/or FNs and of the distance from the position where it should be located [3] [4], as illustrated in Fig. 1 with arrows.…”

Section: On Existing Normalized Measuresmentioning

confidence: 99%

“…In the domain of shape positioning area, alternative dissimilarity measures, inspired from the Hausdorff distance [1], have been proposed in the literature, see [1][2][11] [3]. The majority represents non-normalized measures.…”

Section: On Existing Normalized Measuresmentioning

confidence: 99%

See 2 more Smart Citations

A New Normalized Method of Object Shape-based Recognition and Localization

Moradi¹,

Abdulrahman²,

Magnier³

2019

10th International Conference on Pattern Recognition Systems (ICPRS-2019)

View full text Add to dashboard Cite

This paper introduces a new normalized measure for the assessment of a contour-based object pose. This algorithm allows a supervised assessment of recognition and localization of known objects, the differences between a reference edge map and a candidate image are quantified by computing a performance measure. This measure is normalized and is able determine the degree to which an object shape differs from a desired position. Compared to 6 other approaches, experiments on real images at different sizes/scales exhibit the suitability of the new method for an object pose or shape matching estimation.

show abstract

A novel intrarenal multimodal 2D/3D registration algorithm and preliminary phantom study

Jin

Zhang

et al. 2023

J Applied Clin Med Phys

View full text Add to dashboard Cite

Retrograde intrarenal surgery (RIRS) is a widely utilized diagnostic and therapeutic tool for multiple upper urinary tract pathologies. The image-guided navigation system can assist the surgeon to perform precise surgery by providing the relative position between the lesion and the instrument after the intraoperative image is registered with the preoperative model. However, due to the structural complexity and diversity of multi-branched organs such as kidneys, bronchi, etc., the consistency of the intensity distribution of virtual and real images will be challenged, which makes the classical pure intensity registration method prone to bias and random results in a wide search domain. In this paper, we propose a structural feature similarity-based method combined with a semantic style transfer network, which significantly improves the registration accuracy when the initial state deviation is obvious. Furthermore, multi-view constraints are introduced to compensate for the collapse of spatial depth information and improve the robustness of the algorithm. Experimental studies were conducted on two models generated from patient data to evaluate the performance of the method and competing algorithms. The proposed method obtains mean target error (mTRE) of 0.971 ± 0.585 mm and 1.266 ± 0.416 mm respectively, with better accuracy and robustness overall. Experimental results demonstrate that the proposed method has the potential to be applied to RIRS and extended to other organs with similar structures.

show abstract

Edge detection: a review of dissimilarity evaluations and a proposed normalized measure

Cited by 22 publications

References 52 publications

Shape Similarity Measurement for Known-Object Localization: A New Normalized Assessment

Shape Similarity Measurement for Known-Object Localization: A New Normalized Assessment

A New Normalized Method of Object Shape-based Recognition and Localization

A novel intrarenal multimodal 2D/3D registration algorithm and preliminary phantom study

Contact Info

Product

Resources

About