Piet Dewaele

Texture analysis anno 1983

Abstract In this paper the texture analysis methods being used at present are reviewed. Statistical as well as structural approaches are included and their performances are compared. Concerning the former approach, the gray level difference method, filter mask texture measures, Fourier power spectrum analysis, cooccurrence features, gray level run lengths, autocorrelation features, methods derived from texture models, relative extrema measures, and gray level profiles are discussed. Structural methods which describe texture by its primitives and some placement rules are treated as well. Attention has to be paid to some essential preprocessing steps and to the influence of rotation and scale on the texture analysis methods. Finally the problem of texture segmentation is briefly discussed.

Speckle filtering of synthetic aperture radar images: A review

Abstract Speckle, appearing in synthetic aperture radar (SAR) images as granular noise, is due to the interference of waves reflected from many elementary scatterers. Speckle in SAR images complicates the image interpretation problem by reducing the effectiveness of image segmentation and classification. To alleviate deleterious effects of speckle, various ways have been devised to suppress it. This paper surveys several better‐known speckle filtering algorithms. The concept of each filtering algorithm and the interrelationship between algorithms are discussed in detail. A set of performance criteria is established and comparisons are made for the effectiveness of these filters in speckle reduction and edge, line, and point target contrast preservation using a simulated SAR image as well as airborne and spaceborne SAR images. In addition, computational efficiency and implementation complexity are compared. This critical evaluation of speckle suppression filters is mostly new and is presented as a survey p...

Lily: A Software Package for Image Processing

In this paper we will present LILY, a software package for image processing. LILY stands for Leuven Image processing LibrarY and has been developed with funding from a large number of Belgian industrial companies who are all interested in visual inspection problems. Therefore, the algorithms in the package are mainly concerned with this application field, although also other algorithms are incorporated. All procedures have been written in Pascal and Fortran on a VAX running VMS, with current work being done to convert the package to the C-language. Along with the programmed algorithms come a large number of support functions and procedures to facilitate the development of image processing programs. The package thus presents itself to the user as a large toolbox from which the appropriate tools must be taken to accomplish a certain task. The available procedures fall in one of the following categories: segmentation, coding, filtering, feature extraction, classification, texture analysis, relaxation, and pyramidal structures. In the first part of the paper, an overview will be given of the algorithms that are present in all these different classes. Syntactical conventions, documentation, maintenance and development tools will be discussed also. The second part of the paper is devoted to some specific problems that have been solved as a testcase for the algorithms. First Laws procedure for texture segmentation is implemented and applied to the detection of defects in textiles. The procedure involves filtering the image with one or more suitably chosen masks, squaring the obtained values, computing the energy as a texture feature and classifying the resulting values. Each of these steps corresponds more or less to a different module of the package. A second industrial problem of defect inspection in unexposed radiographic film has been approached using three alternative techniques: one dimensional convolution filtering, Fourier domain filtering and polynomial regression.

An Application Of The LILY Software Package To Defect Inspection In Unexposed Radiographic Film

The results of three visual inspection techniques, using laser light, for defect detection in unexposed radiographic film are presented and compared. First convolution techniques are discussed. An appropriate choice of mask coefficients is explained and the mask dimension has to be matched with the scale at which the errors occur. Second an error detection method using polynomial regression was experienced to be very effective. Finally, fourier filtering can equally well be applied but it was computationally more expensive than the convolution method for this type of inspection. Experiments have been carried out using the LILY software package for image processing.