Hough Transform Processing in 3D Object Detection and Visualization

Fernández, Ariel; Llaguno, Juan M.; Alonso, Julia R.

doi:10.1364/3d.2021.3f2a.5

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…The algorithm works without point cloud retrieval and avoids errors that might arise under this technique. Unlike previous approaches based only in stereo vision capture [34] and mostly aimed at spherical object detection [35], Integral Imaging provides a basis for robust pattern recognition as well as visualization of arbitrary 3D objects under full parallax.…”

Section: Introductionmentioning

confidence: 99%

Generalized Hough transform for 3D object recognition and visualization in integral imaging

2023

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Object recognition is an automated image processing application of great interest in areas ranging from defect inspection to robot vision. In this regard, the generalized Hough transform is a well-established technique for the recognition of geometrical features even when they are partially occluded or corrupted by noise. To extend the original algorithm—aimed at detecting 2D geometrical features out of single images—we propose the robust integral generalized Hough transform, which corresponds to transformation under the generalized Hough transform of an elemental image array obtained from a 3D scene under integral imaging capture. The proposed algorithm constitutes a robust approach to pattern recognition in 3D scenes that takes into account information obtained not only from the individual processing of each image of the array but also from the spatial restrictions arising from perspective shifts between images. The problem of global detection of a 3D object of given size, position, and orientation is then exchanged under the robust integral generalized Hough transform for a more easily solved maximum detection in an accumulation (Hough) space dual to the elemental image array of the scene. Detected objects can then be visualized following refocusing schemes of integral imaging. Validation experiments for the detection and visualization of partially occluded 3D objects are presented. To the best of our knowledge, this is the first implementation of the generalized Hough transform for 3D object detection in integral imaging.

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Section: Introductionmentioning

confidence: 99%

Generalized Hough transform for 3D object recognition and visualization in integral imaging

2023

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Generalized Hough Transform for 3D Object Recognition and Visualization in Integral Imaging

Fernández¹,

Umpiérrez²,

Alonso³

2023

Preprint

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Object recognition is an automated image processing application of great interest in areas ranging from defect inspection to robot vision. In this regard, the Generalized Hough Transform is a well-established technique for the recognition of geometrical features even when they are partially occluded or corrupted by noise. In order to extend the original algorithm -aimed at detecting 2D geometrical features out of single images- we propose the Robust Integral Generalized Hough Transform which corresponds to the transformation under Generalized Hough Transform of an array of Elemental Images taken from a 3D scene in Integral Imaging capture. The proposed algorithm constitutes a robust approach to pattern recognition in 3D scenes that takes into account information obtained not only from the individual processing of each image of the array but also from the spatial restrictions arising from perspective shifts between images. The problem of global detection of a 3D object of given size, position and orientation is then exchanged under Robust Integral Generalized Hough Transform for a more easily solved maxima detection in an accumulation (Hough) space dual to the array of Elemental Images of the scene. Detected objects can then be visualized following refocusing schemes of Integral Imaging. Validation experiments for the detection and visualization of partially occluded three-dimensional objects are presented. To the best of our knowledge this is the first implementation of Generalized Hough Transform for 3D object detection in Integral Imaging.

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Hough Transform Processing in 3D Object Detection and Visualization

Abstract: We present the detection of partially occluded spherical objects by means of the Circular Hough Transform of stereo pair of the scene. Refocusing after filtering allows then to reconstruct the object at its own depth.

Cited by 2 publications

References 7 publications

Generalized Hough transform for 3D object recognition and visualization in integral imaging

Generalized Hough transform for 3D object recognition and visualization in integral imaging

Generalized Hough Transform for 3D Object Recognition and Visualization in Integral Imaging

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