Le filtre de Canny (ou détecteur de Canny) est utilisé en pour la détection des contours. L'algorithme a été conçu par John Canny en 1986 pour être optimal suivant trois critères clairement explicités :

bonne détection : faible taux d'erreur dans la signalisation des contours,

bonne localisation : minimisation des distances entre les contours détectés et les contours réels,

clarté de la réponse : une seule réponse par contour et pas de faux positifs

Développement du filtre de Canny Mise en œuvre Réduction du bruit vignette|Image obtenue après application d'un flou gaussien 5x5. La première étape est de réduire le bruit de l'image originale avant d'en détecter les contours. Ceci permet d'éliminer les pixels isolés qui pourraient induire de fortes réponses lors du calcul du gradient, conduisant ainsi à de faux positifs. Un gaussien 2D est utilisé (voir l'article ), dont voici l'opérateur de convolution : : \mathrm{G}(x,y) = \frac{1}{2

Edge Defect Detection in Ceramic Tile Based on Boundary Analysis Using Fuzzy Thresholding and Radon Transform

Gelareh Mohammadi, Mohsen Pashna

Applying image processing technology and machine vision in industry have had significant development in recent decade. Tile and ceramic industry was not excluded form this matter. By using image processing techniques in production line of this industry, it is possible to detect surface defections such as edge defections, cracks and coloring defections. Surface defection is the most common type of defection in tile and ceramic industry. In this article a new and simple approach for detecting surface defections using Fuzzy thersholding and morphological operand and Radon transforms as well as boundary analysis is introduced. The available algorithm in the articles has good ability in determining number and place of defections and displaying them. Compared with results of other methods, the used algorithm in this article has better results on actual data base, in presence of camera noise and environmental lighting effects.

2008

Exploiting Multi-Temporal Information for SAR Image Segmentation

François Aspert, Meritxell Bach Cuadra, Jean-Philippe Thiran

Earth observation is taking more and more importance in our society. Indeed, recent technologies march allows for satellite images to get ground resolution up to less than one meter. Thus, most of satellite image information obtained begins now to be widely used for multiple purposes ranging from cartography and mapping to agricultural management and security applications. Among all the satellite imaging systems, Synthetic Aperture Radar (or SAR) are very interesting for global earth surveillance and monitoring purposes as they can provide data at any time under all weather conditions. However only few work have been done to take advantage of such time robustness properties for retrieving the images main structures. In this study we focused one the particular issue of obtaining an efficient closed region segmentation using multi-temporal SAR image series. To this end, several tools have been developed. In order to remove SAR inherent noise we filtered the image sequences using a multi-temporal anisotropic non-linear diffusion algorithm. Then a new approach of Canny edge detection have been introduced to extract edge features from these vector-valued images. Finally, a region segmentation step has been applied to get closed regions. We demonstrated that for all the methods, exploiting multi-temporal information can improve the results accuracy. Moreover, since some radiometric changes can occur within region due to man intervention or natural diseases we also presented a direct application of region segmentation to retrieve such changes across time series.

2006

Time-Varying Segmentation for Mapping of Land Cover Changes

François Aspert, Meritxell Bach Cuadra, Jean-Philippe Thiran

Among all satellite imaging systems, Synthetic Aperture Radar (SAR) is useful for monitoring purposes, as they provide data at any time under all weather conditions. Today, three spaceborne SAR systems are operational, while by the end of 2007 three further SAR instruments will be launched, thereby allowing to obtain an almost continuous monitoring of the Earth coverage. In order to translate these multi-temporal data into information in an unsupervised (automated) and reliable way, sophisticated algorithms must be available. In the past years several approaches - primarily based on texture analysis and statistical scene estimation - have been proposed for multi-temporal SAR data analysis. Such methods, based on probability density functions, perform well under strictly controlled conditions, but they are often limited with respect to sensor synergy where complex joint probability density functions must be considered - and to the temporal aspect. To address these limitations, an original set of algorithms for the unsupervised multi-temporal SAR data analysis is proposed. To this end, several issues have been tackled: filtering, edge detection, and image segmentation. Moreover, condition sine qua non for the system design, was that i) it is sensor independent, and ii) data from different SAR systems can be ingested without any a-priori knowledge about the probability density function. Basically, the proposed time varying segmentation involves four independent steps. In a first step, a multi-temporal anisotropic non-linear diffusion filter is applied to filter the images which ultimately allow feature extraction. Subsequently, an extension of Canny edge detection algorithm for multi-temporal edge detection is applied, hence obtaining an edge map consistent across the whole sequence of temporal images. In a third step, closed regions are obtained using a two-part coding scheme with the edge map (as side information) and region growing technique (using the multi-temporal stack). Finally, the number of underlying spectral class composing a segment histogram at every frame is estimated, thus detecting changes due to temporal land cover fluctuations. Results are presented based on a set of 16 ENVISAT ASAR Alternating Polarization and Radarsat-1 Fine Beam images acquired between November 2004 and July 2005 for an agricultural (maize and sun flower) area in South Africa.

2007

Time-Varying Segmentation for Mapping of Land Cover Changes

François Aspert, Meritxell Bach Cuadra, Jean-Philippe Thiran

2007

Filtre de Canny

bonne détection : faible taux d'erreur dans la signalisation des contours,

bonne localisation : minimisation des distances entre les contours détectés et les contours réels,

clarté de la réponse : une seule réponse par contour et pas de faux positifs

Edge Defect Detection in Ceramic Tile Based on Boundary Analysis Using Fuzzy Thresholding and Radon Transform

Exploiting Multi-Temporal Information for SAR Image Segmentation

Time-Varying Segmentation for Mapping of Land Cover Changes

Exploiting Multi-Temporal Information for SAR Image Segmentation

Edge Defect Detection in Ceramic Tile Based on Boundary Analysis Using Fuzzy Thresholding and Radon Transform

Time-Varying Segmentation for Mapping of Land Cover Changes