In this paper, we propose a new method of mathematical morphology called Aurora transform. This is a geodesic
reconstruction that only spreads in radial orientations from a center. Thanks to this method, star domains such as blood
vessels in cross sectional planes are extracted even if these regions are often inhomogeneous or some parts of their edges
are not drawn very well. This method has been successfully applied to extract the edges of the aortic root, the ascending
and the descending aorta in cross sectional cine-MRI. It has been then compared to the use of some active contours.
MRI appears to be particularly attractive for the study of the Sinuses of Valsalva (SV), however there is no global
consensus on their suitable measurements. In this paper, we propose a new method, based on the mathematical
morphology and combining a numerical geodesic reconstruction with an area estimation, to automatically evaluate the
SV from a cine-MRI in a cross-sectional orientation. It consists in the extraction of the shape of the SV, the detection of
relevant points (commissures, cusps and the centre of the SV), the measurement of relevant distances and in a
classification of the valve as bicuspid or tricuspid by a metric evaluation of the SV. Our method was tested on 23 patient
examinations and radii calculations were compared with a manual measurement. The classification of the valve as
tricuspid or bicuspid was correct for all the cases. Moreover, there are an excellent correlation and an excellent
concordance between manual and automatic measurements for images at diastolic phase (r= 0.97; y = x - 0.02; p=NS;
mean of differences = -0.1 mm; standard deviation of differences = 2.3 mm) and at systolic phase (r= 0.96; y = 0.97 x +
0.80; p=NS ; mean of differences = -0.1 mm; standard deviation of differences = 2.4 mm). The cross-sectional
orientation of the image acquisition plane conjugated with our automatic method provides a reliable morphometric
evaluation of the SV, based on the automatic location of the centre of the SV, the commissure and the cusp positions.
Measurements of distances between relevant points allow a precise evaluation of the SV.
We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, and accurate measurements on global shape characteristics such as straightness and sharpness are obtained.
This paper describes a methodology for thin spikes characterization. Nowadays, its evaluation is performed by visual
control. We propose a method to measure these spikes at a micrometric scale by using ombroscopic image processing.
A spike needs to be mainly conic and its tip must be ogival. The first aspect is evaluated by comparing the spike with an
ideal cone based on spike's contour. To find lines supported by contours, we use the Radon transform. However, due to
irregular contour, we develop an improvement of this transform based on morphological operators. This way, real
segments are found and a correct estimation of an ideal cone can be done.
The second aspect is controlled by measuring the radius of the tip which gives both sharpness and regularity of the tip.
As the following of the curvature is problematic, we use a morphological skeleton on the contour to obtain a structure
similar to a Y. The intersection of these three branches leads to a correct estimation of the circular gauge. An additional
filling criterion validates the result.
This study is successful as the production is correctly classified and precise measures were obtained both in terms of
global characteristics and sharpness.
Corner and junction detection is an important preprocessing step in image registration, data fusion, object recognition, and many other tasks. This work deals with corner and junction detection of characteristic features of the structure resulting from cross-pattern projection. The ultimate aim is to adapt the positions and orientation of the cross-pattern projections to what has been observed. The use of this projected light pattern in the framework of active vision allows us to identify certain points of interest on 3-D objects, to directly acquire a synthesis, which thus permits simplified detection, measurement, recognition, or tracking. We present detection methods for corners and junctions in the context of Hough transform detection.
In this article, a new implementation of active curves algorithms is proposed. It is question of an active region algorithm
based on stationary states of a nonlinear diffusion principle. Its originality is to obtain a set of geometric envelopes in
one pass, with a correspondence between level threshold of the grayscale result and a regularity scale, close to the
original shape. This set of geometric envelopes gives a multiscale representation, from a very regular approximation to a
full detailed and roughest representation. This property is used in a new subpixel circle center estimator developed in the
purpose of distorted contours. Results are very promising as precision is noticeably improved compared to a least mean
squares estimator. This estimator is then pretty well adapted to limit distortions caused by industrial processes.
The subject of this paper is the improvement of measures on imperfect circular forms. Indeed, simple geometric forms
have been well studied in image processing. Thus, articles describing circles on a discrete framework are numerous but
the case of imperfect geometric forms, in return, is hardly ever deepen. However, it is a classical problem in industrial
vision control process to not have a perfect, or perfectly discretized, geometric object due to, notably, manufacturing
process, industrial environment (dust, vibrations, objects displacement, etc.), interferences on acquisition chain
(electronic noise, lenses imperfections, etc. ). The authors present a comparison of measurement methods of circles
characteristics subpixel estimation (center's coordinates and radius) for several distortions (geometric or not). The
estimators proposed are classic least mean squares, 3D Hough algorithms and a method combining a Radon transform
based estimator and a FitzHugh-Nagumo partial differential equation based active region algorithm. The originality of
the method is to furnish a set of geometric envelopes in a single pass from a roughest to a full detailed representation.
Moreover, this multiple active region principle also offers interesting electronic implementation possibilities for real
time image processing for metrology on production chains.
This article deals with the problem of the determination of characteristics of imperfect circular objects on discrete images mainly the radius and center's coordinates. Imperfections are provided by discretization, noise and interior distortions present in some production processes. To this end, a multi-level method based on active contours was developed and tested on, noisy or not, misshaped or not, simulated circles whom centers and radius were known. The adequacy of this approach was tested with several methods, among them several Radon based ones. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform based method, using a description of circles from their tangents, improved thanks to a fitting considering the discrete implementation of Radon transform. Through this study, an active region algorithm based on stationary states of a non linear diffusion principle is proposed. Its originality is to obtain a set of geometric envelopes in one pass, with a correspondence between level threshold of the grayscale result and a regularity scale, more or less close to the original shape. This set of geometric envelopes gives a multiscale representation, from a very regular approximation to a full detailed and roughest representation. Then, a more robust measure of the circle parameters can be computed.
We consider an experimental setup, modelling the FitzHugh-Nagumo equation without recovery term and composed of a 1D nonlinear electrical network made up of discrete bistable cells, resistively coupled. In the first place, we study the propagation of topological fronts in the continuum limit, then in more discrete case. We propose to apply these results to the domain of signal processing. We show that erosion and dilation of a binary signal, can be obtained. Finally, we extend the study to 2D lattices and show that it can be of great interest in image processing techniques.
A dimensional measurement system that also tracks object movements is presented here. The method directly yields the level curves of an object. It is an extension of collimation methods, coupled with the use of structured lighting with features formed from several luminous planes intersecting in a single line. This line defines a set of points of the space at a fixed distance Z0 from the measuring head. The locus of the points of the object where the lighting is reduced to a single line is the level curve sought. The introduction of an asymmetry into the lighting structure permits one to determine the direction as well as an approximate value of the value of the distance to the level curve from a point on the illuminated object. The experiments performed permit one to evaluate the performance of such a system, and suggest future applications.
We present in this paper a new method for implementing geometric moment functions in a CMOS retina. It is based on the computation of the correlation value between the image under analysis and a second image since there is a similarity between the expression of the moment of an image and that of the correlation of two images. The second image which is stored in memory devices in the circuit is approximated by a binary image using a dithering algorithm in order to reduce hardware implementation cost. As a result the value of the moment is also an approximate one. Computer simulations using the COIL 100 Columbia image database on 128x128 pixel images show that the maximal relative error between the approximate and the exact value is less than 1% for moments of order less than 2, and less than 5% for moments of order less than 6. Finally, we have considered an object localization application and quantified the error in the localization due to the use of the approximate moment values instead of the exact values.
This paper proposes a comparative survey on techniques of vision based on invisible structured lighting. We have classified them in three distinct families: InfraRed Structured Light (IRSL), Imperceptible Structured Light (ISL) and Filtered Structured Light (FSL). For each of them, definition, minimal configuration and main applications found in the literature are given. Then, we compare them regarding to several criteria: required equipment, light pattern coding, color analysis, texture analysis, motion analysis, security, use in non-controlled environment. The description is IRSL, ISL and FSL sensors will permit to sum up these techniques; the comparison will permit to evaluate performances and efficiency of each of them. We think that this study could be useful to researchers that are looking for a compromise between stereovision and structured light vision, combining the processing tools extent of the former with the point matching reliability and simplicity of processing of the latter.
Lifting Scheme is actually a widely used second generation multi-resolution technique in image and video processing field. It permits to easily create fast, reversible, separable or no, not necessarily linear, multi-resolution analysis for sound, image, video or even 3D graphics. An interesting feature of lifting scheme is the ability to build adaptive transforms, more easily than with other decompositions. Many works have already be done in this subject, especially in lossless or near-lossless compression framework where there is no orthogonal constraint. However, some applications
as lossy compression or de-noising requires well conditioned transforms. Indeed, this is due to the use of shrinking or
quantization which has not controlled propagation through inverse transform. Authors have recently presented a technique permitting to determine some lifting scheme filters in order to obtain a high level of adaptivity combined with near-orthogonal properties, useful for most of these applications. Naturly coming into the adaptive near orthogonal framework, the point of interest of this article is affine algebraic filters. Color images and video have especially been
studied through point of view of compression. In this way, the treatment of the vector aspect of signal, not only by processing channels independently, becomes the focus point of the article.
Since few years, Lifting Scheme has proven its utility in compression field. It permits to easily create fast, reversible, separable or no, not necessarily linear, multiresolution analysis for sound, image, video or even 3D graphics. An interesting feature of lifting scheme is the ability to build adaptive transforms for compression, more easily than with other decompositions. Many works have already be done in this subject, especially in lossless or near-lossless
compression framework : better compression than with usually used methods can be obtained. However, most of the techniques used in adaptive near-lossless compression can not be extended to higher lossy compression rates, even in the simplest cases. Indeed, this is due to the quantization error introduced before coding, which has not controlled propagation through inverse transform. Authors have put their interest to the classical Lifting Scheme, with linear
convolution filters, but they studied criterions to maintain a high level of adaptivity and a good error propagation through inverse transform. This article aims to present relatively simple criterion to obtain filters able to build image and video compression with high compression rate, tested here with the Spiht coder. For this, upgrade and predict filters are simultaneously adapted thanks to a constrained least-square method. The constraint consists in a near-orthogonality inequality, letting sufficiently high level of adaptivity. Some compression results are given, illustrating relevance of this method, even with short filters.
A dimensional measurement system also doing a tracking of objects movements is presented here. Especially, the method presented here permits to directly get the level curves of an object. It's an extension of the measurement methods by collimation, coupled with the use of a structured lighting with signature, formed of several luminous plans competing in a unique line. This line defines a set of points of the space at a fixed distance Z0 of the measure head. The place of the points of the object where the lighting is reduced to a unique line is the searched level curve. The introduction of an asymmetry in the structure of the lighting permits to know the way as well as an approximate value of the value of the gap to the level curve of the position of the point of the illuminated object. The realized experiences permit to place the performances of such a system, and give the field of future applications.
Scanning techniques combining laser line projection with motion are simple and efficient. But there are number of cases in which laser triangulation fails. Some have well known solutions. Other, like adverse illumination by intense white light or presence of textures make laser projection hard to distinguish, and have no specific solution. In this article, a method is presented to improve retrieving laser projection for those cases. It’s build upon two main ideas. First, using auxiliary lines to create local high frequencies. Second, Transform a high speed camera in an intensity modulation receiver. The principle is to send a periodic message in the lines intensity and try to track traces of a spatial-temporal deforming pattern in the video sequences produced by the camera. It permits two main improvements. First, when adverse illumination produce other lines, they can be discriminate by the fact they don’t send the message. Second, when adverse illumination produce a highly luminous image or when a texture diffuse a part of the laser energy, it’s sufficient to track the noise of the message. By choosing a message, it’s possible to create every type of noise in order to distinguish it between the rest of image noises.
This paper describes an application of the visual servoing approach to vision-based control in robotics. The basic idea addresses the use of a vision sensor in the feedback loop within the controlled vision framework. It consists in tracking of arbitrary 3-D objects travelling at unknown velocities in a 2-D space (depth is given as known). Once the necessary modeling stage is performed, the framework becomes one of automatic control, and naturally stability, performance and robustness questions arise. Here, we consider to track line segments corresponding to the edges extracted from the image being analyzed. Two representations for a line segment are presented and discussed, and an appropriate representation is derived. A SISO (Single Input Single Output) model for each parameter of a line segment is then derived and represented by an orthonormal Laguerre network put in state space form. The appeal of this new approach is that it eliminates the need for assumption about the plant order, the time delay and the unmodeled dynamics. For modeling by Laguerre filters, The system must be stable. This problem is handled by an input output data filtering. Hence the poles of filtered model are relocated inside the unit circle. A simple adaptive predictive control is then used for its simplicity. To illustrate the advantages of using the Laguerre network associated to an adaptive input output data filtering, over the conventional control techniques, we carry out a comparison on simulated examples to a PID controller.