Alessandro Gherardi

Multi‐image based method to correct vignetting effect in light microscopy images

Vignetting is the radial attenuation effect of the images brightness intensity from the center of the optical axis to the edges. To perform quantitative image analyses it is mandatory to take into account this effect, intrinsic of the acquisition system. Many image processing steps, such as segmentation and object tracking, are strongly affected by vignetting and the effect becomes particularly evident in mosaicing. The most common approach to compensate the attenuation of the images brightness intensity is to estimate the vignetting function from a homogeneous reference object, typically an empty field, and to use it to normalize the images acquired under the same microscope set‐up conditions. However, several reasons lead to the use of image‐based methods to estimate the vignetting function from the images themselves. In this work, we propose an effective multi‐image based method suitable for real‐time applications. It is designed to correct vignetting in wide field light microscopy images. The vignetting function is computed stemming from a background built incrementally from the proposed background segmentation algorithm, validated on several manually segmented images. The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that our method almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.

Vignetting correction by exploiting an optical microscopy image sequence

Vignetting is one of the most common problem that may affect digital imaging. The effect becomes particularly evident when images are stitched together to increase the cameras field of view (e.g., when building a mosaic), where it can lead to errors in automatic analyses. To correct the effect, the most common approach is to acquire an empty field image in advance that is used later to perform a flat field correction on every subsequently acquired image. However, in several cases, such as when dealing with off-line images or with real time acquisitions, this is not a viable option. The method we propose relies on a non parametric model to characterize in real time the vignetting function from the specimen itself, by using our foreground/background segmentation algorithm. The function is computed over a background built incrementally, detecting regions free of objects of interest. The experiments carried out using cell cultures and histological samples prove that our method yields results at least comparable to those achieved by using empty field.

Automatic Perspective Camera Calibration Based on an Incomplete Set of Chessboard Markers

The measurement in metric units from a perspective view of a real world object is an important task in many computer vision applications. The goal of the perspective calibration is to map the reference coordinates of the 3D object into the 2D image coordinates. This is usually done by recovering the perspective transformation parameters by presenting to the camera a view of a known calibration pattern. Many of the available algorithms require to process all the points of the calibration pattern in order to recover the transformation parameters effectively. The approach we present for the computation of the inverse perspective transformation does not require to consider all the grid points. Rather, a grid matching between the 3D points projection and the model is performed exploiting a graph based approach. Extensive experiments have proved the efficacy of the algorithm in different application fields such as camera calibration and automotive headlight beam characterization.

Illumination field estimation through background detection in optical microscopy

Automated microscopic image analysis techniques are increasingly gaining attention in the field of biological imaging. The success of these applications mostly depends on the earlier image processing steps applied to the acquired images, aiming at enhancing image content while performing noise and artifacts removal. One such artifact is the vignetting effect that in general occurs in most imaging sensors due to an uneven illumination of the scene being imaged. As a consequence, images are usually lighter near the optical center and darker at image borders. This effect is particularly evident when stitching images into a mosaic in order to increase the field of view of the microscope. The existing approaches deal with either the parametric model of the known light distribution or the estimation of the illumination field based on just one image or a sequence of empty-field images. These approaches are only feasible when the acquisition apparatus is at ones disposal. We propose a non parametric and general purpose approach, without using prior information about the light distribution, where the illumination field is estimated from the background, that is built automatically stemming from a sequence of images containing even the objects of interest.

Age-related skin analysis by capacitance images

The skin surface characterization has a great importance for dermatologists as well as for cosmetic scientists in order to evaluate the effectiveness of medical or cosmetic treatments. Skin topography characterization has been faced by using profilometers and skin replicas to achieve some measurements related to either skin 3D profile or wrinkles. So far, no in vivo measurements regarding skin topography changes have been achieved to evaluate skin ageing. This work describes how a portable capacitive device, normally used for fingerprint acquisition, can be utilized to achieve measures of skin ageing routinely. The capacitive images give a high resolution representation of skin topography, in terms of wrinkles and cells. In this work we have addressed the latter: cells have been segmented using the watershed approach and a feature related to their area distribution has been generated. Accurate experiments accomplished in vivo show how the feature we conceived is linearly related to skin ageing.

A robust approach to reconstruct experimentally the camera response function

Many methods are known in literature to reconstruct the camera response function (RF), whether they use calibration chart or images of arbitrary scenes taken at different exposures. This works in case to have at ones disposal a camera with enough exposure steps to capture the whole dynamic range of the scene, representatively. However, in case of entry-level or low quality cameras, the resolution in the shutter time range of variation could yield just a reduced set of samples. Here we propose additional constraints to a well known method to reconstruct a RF even in the case that just a reduced set of exposures is available. Extensive experiments carried out using both a low quality and a professional camera commonly used in computer vision applications show the improvement achieved by our method in the reconstructed RF in case of few samples.

Studying skin ageing through wavelet-based analysis of capacitive images

The skin care retains a great importance for both aesthetics and health. Nowadays, many different approaches are known to quantify the skin health status by analyzing the skin appearance. However, most of these methods are still grounded on surface replicas, or on the use of devices that are not suitable for a routine approach. Also not all the methods are designed to achieve results in an automatic manner. The work presented here describes a method to extract an age-related feature from high resolution capacitive map of the human skin achieved by a portable device. Skin surface samples of 87 subjects have been analyzed in vivo and automatically through using wavelet decomposition. After that samples have been enhanced, we devised a feature, which correspond to the energy of the wavelet coefficients at the finest scale. Experiments prove that the feature we extracted is linearly related to skin ageing.

Real-time whole slide mosaicing for non-automated microscopes in histopathology analysis.

Context: Mosaics of Whole Slides (WS) are a valuable resource for pathologists to have the whole sample available at high resolution. The WS mosaic provides pathologists with an overview of the whole sample at a glance, helping them to make a reliable diagnosis. Despite recent solutions exist for creating WS mosaics based, for instance, on automated microscopes with motorized stages or WS scanner, most of the histopathology analysis are still performed in laboratories endowed with standard manual stage microscopes. Nowadays, there are lots of dedicated devices and hardware to achieve WS automatically and in batch, but only few of them are conceived to work tightly connected with a microscope and none of them is capable of working in real-time with common light microscopes. However, there is a need of having low-cost yet effective mosaicing applications even in small laboratories to improve routine histopathological analyses or to perform remote diagnoses. Aims: The purpose of this work is to study and develop a real-time mosaicing algorithm working even using non-automated microscopes, to enable pathologists to achieve WS while moving the holder manually, without exploiting any dedicated device. This choice enables pathologists to build WS in real-time, while browsing the sample as they are accustomed to, helping them to identify, locate, and digitally annotate lesions fast. Materials and Methods: Our method exploits fast feature tracker and frame to frame registration that we implemented on common graphics processing unit cards. The system work with common light microscopes endowed with a digital camera and connected to a commodity personal computer. Result and Conclusion: The system has been tested on several histological samples to test the effectiveness of the algorithm to work with mosaicing having different appearances as far as brightness, contrast, texture, and detail levels are concerned, attaining sub-pixel registration accuracy at real-time interactive rates.

Measuring Skin Topographic Structures through Capacitance Image Analysis

In dermatology and in cosmetic science, the detailed analysis of the skin surface is still a key requirement to evaluate the effectiveness of medical or cosmetic treatments. Nowadays, the assessment of skin surface topographic structures such as wrinkles or micro-relief 3D profile is mainly obtained by profilometric analysis. Even though such an analysis gives a high level of detail, it is not suitable for in vivo studies since it requires the use of silicone cast replica of the skin. However, in the last few years a portable capacitive device has been proposed for in vivo skin topography characterization. This work presents the method we have developed to assess the capability of the capacitive device to provide reliable absolute measures of the skin surface structures. Extensive experiments carried out by comparing the measures achieved by means of the capacitive device and an optical profilometer allow us to validate our method.

An Automatic System for the Real-Time Characterization of Vehicle Headlamp Beams Exploiting Image Analysis

A vehicles headlamp orientation and luminous and geometrical beam properties are a matter that is strictly ruled by the European Commission for transportation. To test the headlamps, a test system is usually manually aligned to the vehicle, and the human being has the definite opinion even on the beam-related measures. This paper presents a fully automatic system that exploits vision-based technology to extract the geometric parameters of the light profiles that are projected by vehicle headlamps in real time. The 3-D orientation of the longitudinal axis of the vehicle is recovered using stereoscopy. Furthermore, image analysis is used to automatically characterize the shadow-light border of a beam profile, as it would be perceived by an experienced human operator. A locally adaptive thresholding algorithm allows our system to automatically adjust to a wide range of light sources of different power. The alignment procedure and the beam characterization algorithm have been assessed through proper measuring apparatus that is capable of yielding accurate ground-truth data. In particular, the headlamp has been mounted on a special three-axis numerical control unit whose accuracy has been previously assessed, again using image analysis. Experimental results, which are carried out on a large number of different headlamps, show that our method is able to achieve accurate measurements in compliance with current regulations. Finally, it is worth remarking that our solution is fully automatic, and it just requires a simple setup procedure.