Thierry Sentenac

Evaluation of a charge-coupled-device-based video sensor for aircraft cargo surveillance

We present a new video sensor for multimeasurements in an aircraft cargo compartment called a video sensor unit (VSU). This sensor, based on CCD technology, operates in the near IR (NIR) spectral band to measure temperatures due to overheating and fire events. After a characterization of the measurement chain, a radiometric model is applied to the VSU, enabling the measurement of temperatures ranging from 350 to 900 degreesC with a noise equivalent temperature difference (NETD) lower than +/- 8 degreesC. In the same spectral band (NIR), the VSU can also detect smoke and 3-D load displacements. The geometric model of the VSU is described and the associated calibration procedure is presented.

Near infrared thermography with silicon FPA - Comparison to MWIR and LWIR thermography

An ideal thermographic camera could be defined as an uncooled system with high spatial and thermal resolutions featuring a video frame rate, and a short calibration process. In this paper a measurement system based on Silicon FPA operating in the Near Infrared spectral band (0.7 - 1.1 µm) is proposed. This system offers an excellent spatial resolution, a low cost and compactness. With a specific radiometric model, this system can accurately measure temperatures, in a broad temperature range, from 400 up to 1000°C. A comparison with two commercial infrared cameras is performed between 400 and 700°C.

Automated exterior inspection of an aircraft with a pan-tilt-zoom camera mounted on a mobile robot

Abstract. This paper deals with an automated preflight aircraft inspection using a pan-tilt-zoom camera mounted on a mobile robot moving autonomously around the aircraft. The general topic is image processing framework for detection and exterior inspection of different types of items, such as closed or unlatched door, mechanical defect on the engine, the integrity of the empennage, or damage caused by impacts or cracks. The detection step allows to focus on the regions of interest and point the camera toward the item to be checked. It is based on the detection of regular shapes, such as rounded corner rectangles, circles, and ellipses. The inspection task relies on clues, such as uniformity of isolated image regions, convexity of segmented shapes, and periodicity of the image intensity signal. The approach is applied to the inspection of four items of Airbus A320: oxygen bay handle, air-inlet vent, static ports, and fan blades. The results are promising and demonstrate the feasibility of an automated exterior inspection.

Noise effect on the interpolation equation for near infrared thermography

This paper investigates the performance of interpolation equations for a near infrared thermal imager operating over wavelengths from 0.9??m to 1.7??m with various filter bandwidths and a broad temperature range from 300??C to 1000??C. The equations are based on a general formulation of the effective wavelength as a function of the temperature. The quality of the interpolation is assessed in relation to the order of the effective wavelength. However, the noise induced by the imperfections of the thermal imager significantly disturbs the signal, and this phenomenon is enhanced as the bandwidth of the filter increases (i.e. for low-temperature applications). The main purpose of this paper is to establish the right choice of the filter bandwidth and the expression and order of the interpolation equation in relation to the noise level on the thermal imager and the desired accuracy. This paper first outlines the background on interpolation equations and then tests them on synthetic data from signals delivered first by an ideal thermal imager (i.e. free from noise) and then from noisy signals. This simulation study provides a framework for users to select an interpolation equation with an adequate order for near infrared thermal imagers. The performances of the selected interpolation equations are finally demonstrated on real images performed by a near infrared thermal imager.

A navigational framework combining Visual Servoing and spiral obstacle avoidance techniques

This paper presents a navigational framework which enables a robot to perform Long Range Navigation in the context of the Air-Cobot-Project in which a robot is used to execute an autonomous pre-flight inspection on an aircraft. The robot is equipped with Laser range finders and a mobile stereo camera system. The idea is to guide the robot to the pre-defined checkpoints using a Visual Servoing controller based on video data, while avoiding static and moving obstacles. The contribution of the paper is an avoidance technique derived from the spiral flight path of insects applied to the Laser range data. Simulation results validate the whole approach.

Overheating, flame, smoke, and freight movement detection algorithms based on charge-coupled device camera for aircraft cargo hold surveillance

We introduce a new approach to aircraft cargo compartment surveillance. The originality of the approach is in the use of a single sensor type, a CCD camera, to detect fire events and freight movement in aircraft cargo holds (multiphenomenom/monosensor approach). The CCD camera evaluation and the radiometric and geometric models are provided in (Sentenac et al., 2002). We go on to discuss the image analysis algorithms used in the detection of fire signatures (hot spots, flame, and smoke) and load displacement. For each phenomenon, the discriminant parameters are established and the algorithm is explained. The crucial factor is the validation procedure according to aeronautical standards. The experimental trials were carried out in a test chamber providing the fire and smoke test facilities [TF1 to TF6 following EN 54 (Afnor, 1997) requirements].

Matching CAD Model and Image Features for Robot Navigation and Inspection of an Aircraft

This paper focuses on the navigation of a moving robot equipped with cameras, moving around an aircraft to perform inspection of different types of items (probes, doors, etc.). Matching CAD model and image features is useful to provide meaningful features for localization and inspection tasks. In our approach two primitive sets are matched using a similarity function. The similarity scores are injected in the edges of a bipartite graph. A best-match search procedure in bipartite graph guarantees the uniqueness of the match solution. The method provides good matching results even when the location of the robot with respect to the aircraft is badly estimated. Inspection approaches on static ports and air inlet vent are presented.

Rank-Constrained Fundamental Matrix Estimation by Polynomial Global Optimization Versus the Eight-Point Algorithm

The fundamental matrix can be estimated from point matches. The current gold standard is to bootstrap the eight-point algorithm and two-view projective bundle adjustment. The eight-point algorithm first computes a simple linear least squares solution by minimizing an algebraic cost and then projects the result to the closest rank-deficient matrix. We propose a single-step method that solves both steps of the eight-point algorithm. Using recent results from polynomial global optimization, our method finds the rank-deficient matrix that exactly minimizes the algebraic cost. In this special case, the optimization method is reduced to the resolution of very short sequences of convex linear problems which are computationally efficient and numerically stable. The current gold standard is known to be extremely effective but is nonetheless outperformed by our rank-constrained method for bootstrapping bundle adjustment. This is here demonstrated on simulated and standard real datasets. With our initialization, bundle adjustment consistently finds a better local minimum (achieves a lower reprojection error) and takes less iterations to converge.

Airplane tire inspection by image processing techniques

In this paper, we propose a new approach to detect and inspect airplane tires. We use normalized correlation based template matching to detect tires and GrabCut segmentation method to extract them from the background. We inspect the tires condition by investigating the tire treads. Ridge based intensity profiling gives satisfying inspection results.

Automated visual inspection of an airplane exterior

This paper deals with the inspection of an airplane using a Pan-Tilt-Zoom camera mounted on a mobile robot moving around the airplane. We present image processing methods for detection and inspection of four different types of items on the airplane exterior. Our detection approach is focused on the regular shapes such as rounded corner rectangles and ellipses, while inspection relies on clues such as uniformity of isolated image regions, convexity of segmented shapes and periodicity of the image intensity signal. The initial results are promising and demonstrate the feasibility of the envisioned robotic system.