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

Moradi, Behrang; Abdulrahman, Hasan; Magnier, Baptiste

doi:10.1049/cp.2019.0246

Cited by 1 publication

(1 citation statement)

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“…This paper presents a new approach for the measurement of a contour-based object pose, which is normalized. It follows on from a talk given by the research team in [ 2 ], dealing with the subject more thoroughly and in greater detail. The proposed measurement evaluates an estimated supervised score for the shape representation based on the weights created by both false positive and false negative edge pixels.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

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

Magnier

Moradi

2019

J. Imaging

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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.

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Section: Introduction and Motivationsmentioning

confidence: 99%