Showing papers by "José A. Ferrari published in 2015"

Color-fringe pattern profilometry using a generalized phase-shifting algorithm.

Abstract: In order to overcome the limitations of the sequential phase-shifting fringe pattern profilometry for dynamic measurements, a color-channel-based approach is presented. The proposed technique consists of projecting and acquiring a colored image formed by three sinusoidal phase-shifted patterns. Therefore, by using the conventional three-step phase-shifting algorithm, only one color image is required for phase retrieval each time. However, the use of colored fringe patterns leads to a major problem, the color crosstalk, which introduces phase errors when conventional phase-shifting algorithms with fixed phase-shift values are utilized to retrieve the phase. To overcome the crosstalk issue, we propose the use of a generalized phase-shifting algorithm with arbitrary phase-shift values. The simulations and experimental results show that the proposed algorithm can significantly reduce the influence of the color crosstalk.

All-in-focus image reconstruction under severe defocus.

Abstract: Limited depth-of-focus is a problem in many fields of optics, e.g., microscopy and macro-photography. We propose a new physically based method with a space variant point spread function (PSF) to accomplish all-in-focus reconstruction (image fusion) from a multi-focus image sequence in order to extend the depth-of-field. The proposed method works well under strong defocus conditions for color image stacks of arbitrary length. Experimental results are provided to demonstrate that our method outperforms state-of-the-art image fusion algorithms for strong defocus on both synthetic as well as real data images.

Real-time pattern recognition using an optical generalized Hough transform.

Abstract: We present some pattern recognition applications of a generalized optical Hough transform and the temporal multiplexing strategies for dynamic scale and orientation-variant detection. Unlike computer-based implementations of the Hough transform, in principle its optical implementation does not impose restrictions on the execution time or on the resolution of the images or frame rate of the videos to be processed, which is potentially useful for real-time applications. Validation experiments are presented.

Optical implementation of the generalized Hough transform with totally incoherent light.

Abstract: The generalized Hough transform is a well-established technique for detecting complex shapes in images containing noisy or missing data. We present an efficient optical implementation of this transform using an electrical lens with variable focal length and a rotating pupil mask matching the pattern to be found. The proposed setup works under fully (i.e., both spatially and temporally) incoherent illumination and can handle orientation changes or scale variations in the pattern. Validation experiments showing its real-time application are presented.

Wrapping-free phase retrieval with applications to interferometry, 3D-shape profiling, and deflectometry.

Abstract: Phase unwrapping is probably the most challenging step in the phase retrieval process in phase-shifting and spatial-carrier interferometry. Likewise, phase unwrapping is required in 3D-shape profiling and deflectometry. In this paper, we present a novel phase retrieval method that completely sidesteps the phase unwrapping process, significantly eliminating the guessing in phase reconstruction and thus decreasing the time data processing. The proposed wrapping-free method is based on the direct integration of the spatial derivatives of the interference patterns under the single assumption that the phase is continuous. This assumption is valid in most physical applications. Validation experiments are presented confirming the robustness of the proposed method.

Nonplanar fiber-optic sensing head for the compensation of bending-induced birefringence in Faraday current sensors.

Abstract: We demonstrate the compensation of bending-induced linear birefringence in single-mode fibers coiled in a nonplanar path by alternating orthogonal bending planes. This effect can be applied for the construction of birefringence-free fiber coils in Faraday sensor heads (e.g., in current sensors) to improve their sensitivity. Validation experiments are presented.

Real-time Optical Realization of Circle Hough Transform with Incoherent Light

Abstract: We present an optical implementation of the circle Hough transform with an electrical lens with variable focal length and annular pupil. The system works under incoherent light and it is suitable for real-time applications. Validation experimental results are provided.

From Frequency Domain Multi-Focus Fusion to Focus Slicing

Abstract: For optical systems under severe defocus, we propose a method to estimate the focus slices (i.e. in-focus region of each of the acquired images of a stack) from Fourier based all-in-focus reconstructed image. Experimental results are provided.

One-Shot 3D-Gradient Method Applied to Face Recognition

Abstract: In this work we describe a novel one-shot face recognition setup. Instead of using a 3D scanner to reconstruct the face, we acquire a single photo of the face of a person while a rectangular pattern is been projected over it. Using this unique image, it is possible to extract 3D low-level geometrical features without the explicit 3D reconstruction. To handle expression variations and occlusions that may occur (e.g. wearing a scarf or a bonnet), we extract information just from the eyes-forehead and nose regions which tend to be less influenced by facial expressions. Once features are extracted, SVM hyper-planes are obtained from each subject on the database (one vs all approach), then new instances can be classified according to its distance to each of those hyper-planes. The advantage of our method with respect to other ones published in the literature, is that we do not need and explicit 3D reconstruction. Experiments with the Texas 3D Database and with new acquired data are presented, which shows the potential of the presented framework to handle different illumination conditions, pose and facial expressions.

Automatic Eyes and Nose Detection Using Curvature Analysis

Abstract: In the present work we propose a method for detecting the nose and eyes position when we observe a scene that contains a face. The main goal of the proposed technique is that it capable of bypassing the 3D explicit mapping of the face and instead take advantage of the information available in the Depth gradient map of the face. To this end we will introduce a simple false positive rejection approach restricting the distance between the eyes, and between the eyes and the nose. The main idea is to use nose candidates to estimate those regions where is expected to find the eyes, and vice versa. Experiments with Texas database are presented and the proposed approach is testes when data presents different power of noise and when faces are in different positions with respect to the camera.