Visual texture discrimination using random-dot patterns

Visual texture segmentation in cats

The segmentation of visual images on the basis of textural discontinuity was studied in cats using two behavioural paradigms. The first task (Experiment 1) required the animals to detect the presence of a target square of one texture embedded in a background of a second texture. The second task (Experiment 2) required the cats to discriminate between two forms (square and triangle) both of which were defined by texture-texture boundaries. Both detection and discrimination tasks were presented in a transfer paradigm in which the animals first learned a luminance-based form of the same problem. The results indicate that cats are able to segment a visual array on the basis of textural discontinuity in the absence of global luminance differences between figure and ground, and that they are able to use the contour information provided by texture-texture boundaries as a basis for form discrimination.

Structural analysis of natural textures

Many textures can be described structurally, in terms of the individual textural elements and their spatial relationships. This paper describes a system to generate useful descriptions of natural textures in these terms. The basic approach is to determine an initial, partial description of the elements using edge features. This description controls the extraction of the texture elements. The elements are grouped by type, and spatial relationships between elements are computed. The descriptions are shown to be useful for recognition of the textures, and for reconstruction of periodic textures.

A new method for texture fields synthesis: some applications to the study of human vision

We present a general method to synthesize a stochastic process from its a priori given second-order statistics. Some new results, including a new conjecture dealing with visual discrimination of stochastic texture fields, are also given.

Decorrelation methods of texture feature extraction

This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination. A texture feature extraction technique involving autocorrelation function measurement of a texture field, combined with histogram representation of a statistically decorrelated version of the texture field, is introduced. The texture feature extraction method is evaluated in terms of a Bhattacharyya distance measure.

Optical pseudocolor encoding of spatial frequency information

An optical spatial filtering system is described which color encodes the local spatial frequency content of an image. It is shown that partially coherent illumination has advantages over coherent or incoherent illumination in this system. Experimental results are shown which indicate that the system can be used to perform a simple type of texture-to-color conversion. The system could be used to enhance textural differences for a human observer or as a preprocessor which provides texture related information to a second image processing device.