The utility of image descriptions in the initial stages of vision: A case study of printed text

Abstract

Vision research has made very substantial progress towards understanding how we see.It is one area of psychology where the three-way thrust of behavioural measurements (psychophysics), brain imaging, and computational studies have been combined quite routinely for some years. The purpose of this paper is to demonstrate a relatively unusual form of computational modelling which we characterise as involving image descriptions. Image descriptions are statements about structures in images and relationships between structures. Most modelling in vision is either conceived in fairly abstract terms, or is done at the level of images. Neither is entirely satisfactory, and image descriptions are a simple formulation of age-old ideas about a vocabulary of image features that are detected and parameterized from actual digital images.For our example, we use the domain of the visual perception of printed text. This is an area that has been characterized by thorough, robust psychophysical experiments. The fundamental requirements of visual processing in this domain are: grouping of some parts if the image into words; at the same time segmenting words from each other. We show how these are readily understood in terms of our model of image descriptions, and show quantitatively that typographical practice, refined over centuries, is about optimum for the visual system at least as represented by our model. In addition, we show that the same notion of image descriptions could, in principle, support word recognition in certain circumstances.

Horizontal information drives the behavioural signatures of face processing

“…Our research adds another application for the output of oriented receptive fields, as a source of direct evidence to facial identity. This fits into an emerging picture that higher-level visual tasks that elicit high levels of expertise -such as face recognition and reading (Watt and Dakin, 2010) -may be coded to directly exploit the structuring of visual input that emerges from early visual analysis.…”

What is required for a signal to be qualified as a ‘grouping’ tag?

“…In doing so, we should be especially careful about the interpretation of the neural signals: how signals at the borderlines correspond to surface perception and what kind of signals can be qualified as grouping signals. It appears that the 'overlap tokens' proposed by Watt and Dakin (2010a) lack some of the essential properties to be qualified as grouping signals and the new data in their reply (Watt & Dakin, 2010b) do not 'fill the gap'. On the contrary, they rather emphasize the need for grouping signals to reflect the global context of the image, which is missing in their model.…”

“…In our commentary paper (Dry, Kogo, Putzeys, & Wagemans, 2010) on 'The utility of image descriptions in the initial stages of vision: a case study of printed text' (Watt & Dakin, 2010a), we raised a few concerns about the approach to perceptual grouping proposed by Watt and Dakin. Specifically, we argued that the 'overlap tokens' resulting from convolution with Gabor filters do not reflect the global configuration of the image and hence that they would not be able to reproduce cases of context-sensitive perception such as illusory contours in the Kanizsa image.…”

“…In their recent paper 'The utility of image descriptions in the initial stages of vision: a case study of printed text', published in the British Journal of Psychology, Watt and Dakin (2010a) attempt to develop a model, which involves what they believe to be mid-level visual processes. The model reproduces, according to the authors, perceptual grouping by combining the results of the convolution with Gabor filters.…”

“…Now, let us assume that we run Watt and Dakin's model on this simple image. The overlap token will be created along the boundary but not in the interior of the surface because of the nature of the Gabor filters (see Figure 6 in their original paper; Watt & Dakin, 2010a). Are these signals along the boundary qualified as the grouping signals?…”