Using an infrared image sequence, how can one make the inner structure of a sample more visible without human supervision nor understanding of the context? This task is well known as a challenging task. One of the reasons is due to the great number of external events and factors that can influence the acquisition. This paper introduces a solution to this question. The sequence of infrared images is processed using the monogenic signal theory in order to extract the phase congruency. The Fourier Transform must respect the Hermitian property and it does thank to the Hilbert Transform in the 1D case, however this property is not respected in 2D. It does thanks to some approximation made in the analytic signal. The monogenic signal theory consists in reprocessing the Fourier Transform by replacing the Hilbert Transform by a Riesz Transform in order to maintain the Hermitian symmetry. In other words the phase congruence can be described as a feature detection approach. Using the assumption that the symmetry, or asymmetry of the phase does represent the similarity of the features at one scale, then the phase congruency represents how similar the phase values are at different scales. The proposed approach is invariant to image contrast which makes it suitable for applications. It can also give valuable results even with very noisy sequences. The proposed approach has been evaluated by using referenced Carbon Fiber Reinforced Plastic sample.
In this paper, thermographic inspections, ultrasonic C-scan and terahertz imaging were used to detect damages caused by impacts in natural, non-natural and hybrid composites. In particular, different hybrid structures were used. In some samples, numerical simulations were performed to predict the damage. A comparison of the results based on experimental and simulated experiments were afterwards conducted with the aim to explore the inspection capability of each technique.
Long Wavelength Infrared (LWIR) cameras can provide a representation of a part of the light spectrum that is sensitive to temperature. These cameras also named Thermal Infrared (TIR) cameras are powerful tools to detect features that cannot be seen by other imaging technologies. For instance they enable defect detection in material, fever and anxiety in mammals and many other features for numerous applications. However, the accuracy of thermal cameras can be affected by many parameters; the most critical involves the relative position of the camera with respect to the object of interest.
Several models have been proposed in order to minimize the influence of some of the parameters but they are mostly related to specific applications. Because such models are based on some prior informations related to context, their applicability to other contexts cannot be easily assessed. The few models remaining are mostly associated with a specific device.
In this paper the authors studied the influence of the camera position on the measurement accuracy. Modeling of the position of the camera from the object of interest depends on many parameters. In order to propose a study which is as accurate as possible, the position of the camera will be represented as a five dimensions model. The aim of this study is to investigate and attempt to introduce a model which is as independent from the device as possible.
Traditional homomorphic enhancement method is only attributed to the frequency domain processing, which could not enhance the image outline effectively. A better homomorphic algorithm could consider the dynamic range of image to compress and expand gray levels of the target and thus enhance image details. After the frequency domain enhancement, the deployment of mathematical morphology could smooth the outline of the image in spatial domain. This paper develops an effectively comprehensive approach to optimize the contrast of infrared image, utilizing non-linear filtering in frequency domain and top-hat and bottom-hat transforms in spatial domain. Besides, a fuzzy entropy scheme is defined to verify the improved infrared image enhancement effects. Experimental results indicate that, through the proposed method, the image details and contours can be better enhanced comparing with other methods.