* Current address – Department of Industrial Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI 53201 † Corresponding author – [email protected] Tel: +91-80-22932301 Fax: +91-80-23600648 ABSTRACT Surface texture of the die plays an important role on friction during metal forming. In the present study, unidirectional and random surface finishes were produced on hardened stee...

The problem of textured image segmentation upon an unsupervised scheme is addressed. In the past two decades, there has been much interest in segmenting images involving complex random or structural texture patterns. However, most unsupervised segmentation techniques generally suffer from the lack of information about the correct number of texture classes. Therefore, this number is often assume...

This chapter explores the mathematical and algorithmic properties of two sample-based texture models: random phase noise (RPN) and asymptotic discrete spot noise (ADSN). These models permit to synthesize random phase textures. They arguably derive from linearized versions of two early Julesz texture discrimination theories. The ensuing mathematical analysis shows that, contrarily to some statem...

Surveillance of large areas of the Earths surface is often undertaken with low resolution synthetic aperture radar (SAR) imagery from either a satellite or a plane. There is a need to process these images with automatic target detection (ATD) algorithms. Typically the targets being searched for are vehicles or small vessels, which occupy only a few resolution cells. Simple thresholding is usual...

Texture features derived from wavelet transforms have recently been exploited for texture discrimination, image retrieval from a database, region classification for satellite images. Most works demonstrate that the error rate for texture classification is reduced as the number of texture features increases but seldom mentioned how to select good features derived from a specified wavelet transfo...

This paper proposes, applies and evaluates a new technique for texture classification in digital images. The work describes, as far as possible in a quantitative way, the concept of texture in digital images. Furthermore, we developed an innovative model that allows classifying and characterizing texture in digital images, to be used as a useful tool in noninvasive inspection of visual surfaces...

This paper presents an unsupervised texture image segmentation algorithm using reduced Gabor filter set and mean shift clustering. Two criteria are proposed in order to construct a feature space of reduced dimensions for texture image segmentation, based on selected Gabor filter subset from a predefined Gabor filter set. An unsupervised clustering algorithm using the mean shift clustering metho...

In this paper we present the results of two experiments. The first is on the categorization of texture words in the English language. The goal was to determine whether there is a common basis for subjects’ groupings of words related to visual texture, and if so, to identify the underlying dimensions used to categorize those words. Eleven major clusters were identified through hierarchical clust...

With the development of remote sensing techniques, a vast amount of SAR sea ice imagery is being provided by satellite platforms. As an important aspect of measurement, monitoring, and understanding of sea ice evolution during the seasons, the generation of ice type maps is a fundamental step in the interpretation of these data. The abundant texture information in SAR imagery is useful for segm...