Shift in spatial scale in identifying crowded letters

Fonts Designed for Macular Degeneration: Impact on Reading

Purpose

People with macular degeneration (MD) experience difficulties in reading due to central-field loss. Two new fonts, Eido and Maxular Rx, have been designed specifically for individuals with MD. We have compared reading performance of these new fonts with three mainstream fonts (Times-Roman, Courier, and Helvetica).

Methods

Subjects with MD (n = 19) and normally sighted subjects (n = 40) were tested with digital versions of the MNREAD test using the five fonts. Maximum reading speed (MRS), critical print size (CPS), and reading acuity (RA) were estimated to characterize reading performance. Physical properties of the fonts were quantified by interletter spacing and perimetric complexity.

Results

Reading with MD showed font differences in MRS, CPS, and RA. Compared with Helvetica and Times, Maxular Rx permitted both smaller CPS and RA, and Eido permitted smaller RA. However, the two new fonts presented no advantage over Courier. Spacing, but not Complexity, was a significant predictor of reading performance for subjects with MD.

Conclusions

The two fonts, designed specifically for MD, permit smaller print to be read, but provide no advantage over Courier.

Word Mode: a crowding-free reading protocol for individuals with macular disease

Central retinal loss through macular disease markedly reduces the ability to read largely because identification of a word using peripheral vision is negatively influenced by nearby text, a phenomenon termed visual crowding. Here, we present a novel peripheral reading protocol, termed Word Mode, that eliminates crowding by presenting each word in isolation but in a position that mimics its natural position in the line of text being read, with each new word elicited using a self-paced button press. We used a gaze-contingent paradigm to simulate a central scotoma in four normally-sighted observers, and measured oral reading speed for text positioned 7.5° in the inferior field. Compared with reading whole sentences, our crowding-free protocol increased peripheral reading speeds by up to a factor of seven, resulted in significantly fewer reading errors and fixations per sentence, and reduced both the critical print size and the text size required for spot reading by 0.2-0.3 logMAR. We conclude that the level of reading efficiency afforded by the crowding-free reading protocol Word Mode may return reading as a viable activity to many individuals with macular disease.

Stimulus conflation and tuning selectivity in V4 neurons: a model of visual crowding

Visual crowding is a fundamental constraint on our ability to identify peripheral objects in cluttered environments. This study proposes a descriptive model for understanding crowding based on the tuning selectivity for stimuli within the receptive field (RF) and examines potential neural correlates in cortical area V4. For V4 neurons, optimally sized, letter-like stimuli are much smaller than the RF. This permits stimulus conflation, the fusing of separate objects into a single identity, to occur within the RF of single neurons. Flanking interactions between such stimuli were found to be limited to the RF. The response to an optimal stimulus centered in the neuron's RF, is suppressed by the simultaneous presentation of flanking stimuli within the RF. The degree of suppression is a function of the neuron's stimulus tuning properties and the position of the flanker within the RF. A single neuron may show suppression or facilitation depending on the detailed stimulus conditions and the relationship to tuning selectivity. Loss of activity in the set of neurons tuned to a particular stimulus alters its overall representation and potential identification, thus forming a basis for visual crowding effects. The mechanisms that determine the outcome of conflation are associated with object identification, and are not some other independent visual phenomena.

A crowdful of letters: disentangling the role of similarity, eccentricity and spatial frequencies in letter crowding

The present study investigated the joint impact of target-flanker similarity and of spatial frequency content on the crowding effect in letter identification. We presented spatial frequency filtered letters to neurologically intact non-dyslexic readers while manipulating target-flanker distance, target eccentricity and target-flanker confusability (letter similarity metric based on published letter confusion matrices). The results show that high target-flanker confusability magnifies crowding. They also reveal an intricate pattern of interactions of the spatial frequency content of the stimuli with target eccentricity, flanker distance and similarity. The findings are congruent with the notion that crowding results from the inappropriate pooling of target and flanker features and that this integration is more likely to match a response template at a subsequent decision stage with similar than dissimilar flankers. In addition, the evidence suggests that crowding from similar flankers is biased towards relatively high spatial frequencies and that crowding shifts towards lower spatial frequencies as target eccentricity is increased.

From regular text to artistic writing and artworks: Fourier statistics of images with low and high aesthetic appeal

The spatial characteristics of letters and their influence on readability and letter identification have been intensely studied during the last decades. There have been few studies, however, on statistical image properties that reflect more global aspects of text, for example properties that may relate to its aesthetic appeal. It has been shown that natural scenes and a large variety of visual artworks possess a scale-invariant Fourier power spectrum that falls off linearly with increasing frequency in log-log plots. We asked whether images of text share this property. As expected, the Fourier spectrum of images of regular typed or handwritten text is highly anisotropic, i.e., the spectral image properties in vertical, horizontal, and oblique orientations differ. Moreover, the spatial frequency spectra of text images are not scale-invariant in any direction. The decline is shallower in the low-frequency part of the spectrum for text than for aesthetic artworks, whereas, in the high-frequency part, it is steeper. These results indicate that, in general, images of regular text contain less global structure (low spatial frequencies) relative to fine detail (high spatial frequencies) than images of aesthetics artworks. Moreover, we studied images of text with artistic claim (ornate print and calligraphy) and ornamental art. For some measures, these images assume average values intermediate between regular text and aesthetic artworks. Finally, to answer the question of whether the statistical properties measured by us are universal amongst humans or are subject to intercultural differences, we compared images from three different cultural backgrounds (Western, East Asian, and Arabic). Results for different categories (regular text, aesthetic writing, ornamental art, and fine art) were similar across cultures.

Spatial-frequency cutoff requirements for pattern recognition in central and peripheral vision

It is well known that object recognition requires spatial frequencies exceeding some critical cutoff value. People with central scotomas who rely on peripheral vision have substantial difficulty with reading and face recognition. Deficiencies of pattern recognition in peripheral vision, might result in higher cutoff requirements, and may contribute to the functional problems of people with central-field loss. Here we asked about differences in spatial-cutoff requirements in central and peripheral vision for letter and face recognition. The stimuli were the 26 letters of the English alphabet and 26 celebrity faces. Each image was blurred using a low-pass filter in the spatial frequency domain. Critical cutoffs (defined as the minimum low-pass filter cutoff yielding 80% accuracy) were obtained by measuring recognition accuracy as a function of cutoff frequency (in cycles per object). Our data showed that critical cutoffs increased from central to peripheral vision by 20% for letter recognition and by 50% for face recognition. We asked whether these differences could be accounted for by central/peripheral differences in the contrast sensitivity function (CSF). We addressed this question by implementing an ideal-observer model which incorporates empirical CSF measurements and tested the model on letter and face recognition. The success of the model indicates that central/peripheral differences in the cutoff requirements for letter and face recognition can be accounted for by the information content of the stimulus limited by the shape of the human CSF, combined with a source of internal noise and followed by an optimal decision rule.

Object crowding

Crowding occurs when stimuli in the peripheral fields become harder to identify when flanked by other items. This phenomenon has been demonstrated extensively with simple patterns (e.g., Gabors and letters). Here, we characterize crowding for everyday objects. We presented three-item arrays of objects and letters, arranged radially and tangentially in the lower visual field. Observers identified the central target, and we measured contrast energy thresholds as a function of target-to-flanker spacing. Object crowding was similar to letter crowding in spatial extent but was much weaker. The average elevation in threshold contrast energy was in the order of 1 log unit for objects as compared to 2 log units for letters and silhouette objects. Furthermore, we examined whether the exterior and interior features of an object are differentially affected by crowding. We used a circular aperture to present or exclude the object interior. Critical spacings for these aperture and "donut" objects were similar to those of intact objects. Taken together, these findings suggest that crowding between letters and objects are essentially due to the same mechanism, which affects equally the interior and exterior features of an object. However, for objects defined with varying shades of gray, it is much easier to overcome crowding by increasing contrast.

Precision of position signals for letters

Accurate reading of words and text relies on reliable identification of letters in left-to-right order. Previous studies have shown that people often make letter-reversal errors when identifying strings of letters away from fixation. These errors contribute to a decline in letter identification performance away from fixation. This study tests the hypothesis that these errors are due to decreased precision (increased position noise) in the coding of letter position in the periphery. To test our hypothesis, we measured observers' performance for identifying pairs of adjacent letters presented within eight letter positions left and right of fixation. The task was to name the two letters of each pair, from left to right. Responses were scored in two ways for each letter position: (1) letters were identified correctly and in the correct position, and (2) letters were identified correctly but in the wrong position. The ratio of these two scores, when subtracted from 1, gives the empirical rate of mislocation errors. Our primary finding shows that the coding of letter position becomes increasingly imprecise with distance from fixation. A model in which the encoded position of each letter is independent and Gaussian distributed, and in which the spread of the distribution governs the precision of localizing the letter accounts for the empirical rate of mislocation errors. We also found that precision of letter position coding scales with letter size but the precision does not improve with the use of a pre-cue.

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

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 that 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.

Efficient integration across spatial frequencies for letter identification in foveal and peripheral vision

Objects in natural scenes are spatially broadband; in contrast, feature detectors in the early stages of visual processing are narrowly tuned in spatial frequency. Earlier studies of feature integration using gratings suggested that integration across spatial frequencies is suboptimal. Here we re-examined this conclusion using a letter identification task at the fovea and at 10 deg in the lower visual field. We found that integration across narrow-band (1-octave) spatial frequency components of letter stimuli is optimal in the fovea. Surprisingly, this optimality is preserved in the periphery, even though feature integration is known to be deficient in the periphery from studies of other form-vision tasks such as crowding. A model that is otherwise a white-noise ideal observer except for a limited spatial resolution defined by the human contrast sensitivity function and using internal templates slightly wider in bandwidth than the stimuli is able to account for the human data. Our findings suggest that deficiency in feature integration found in peripheral vision is not across spatial frequencies.

Crowding--an essential bottleneck for object recognition: a mini-review

Crowding, generally defined as the deleterious influence of nearby contours on visual discrimination, is ubiquitous in spatial vision. Crowding impairs the ability to recognize objects in clutter. It has been extensively studied over the last 80 years or so, and much of the renewed interest is the hope that studying crowding may lead to a better understanding of the processes involved in object recognition. Crowding also has important clinical implications for patients with macular degeneration, amblyopia and dyslexia. There is no shortage of theories for crowding-from low-level receptive field models to high-level attention. The current picture is that crowding represents an essential bottleneck for object perception, impairing object perception in peripheral, amblyopic and possibly developing vision. Crowding is neither masking nor surround suppression. We can localize crowding to the cortex, perhaps as early as V1; however, there is a growing consensus for a two-stage model of crowding in which the first stage involves the detection of simple features (perhaps in V1), and a second stage is required for the integration or interpretation of the features as an object beyond V1. There is evidence for top-down effects in crowding, but the role of attention in this process remains unclear. The strong effect of learning in shrinking the spatial extent of crowding places strong constraints on possible models for crowding and for object recognition. The goal of this review is to try to provide a broad, balanced and succinct review that organizes and summarizes the diverse and scattered studies of crowding, and also helps to explain it to the non-specialist. A full understanding of crowding may allow us to understand this bottleneck to object recognition and the rules that govern the integration of features into objects.

Crowding between first- and second-order letter stimuli in normal foveal and peripheral vision

Evidence that the detection of first- and second-order visual stimuli is processed by separate pathways abounds. This study asked whether first- and second-order stimuli remain independent at the stage of processing where crowding occurs. We measured thresholds for identifying a first-order (luminance defined) or second-order (contrast defined) target letter in the presence of two second- or first-order flanking letters. For comparison, we also measured thresholds when the target and flanking letters were all first or second order. Contrast of the flankers was 1.6 times their respective contrast thresholds. Measurements were obtained at the fovea and 10 degrees in the lower visual field of four normally sighted observers. Two observers were also tested at 10 degrees nasal visual field. As expected, in both the fovea and periphery, the magnitude of crowding (threshold elevation) was maximal at the closest letter separation and decreased as letter separation increased. The magnitude of crowding was greater for second- than for first-order target letters, independent of the order type of flankers; however, the critical distance for crowding was similar for first- and second-order letters. Substantial crossover crowding occurred when the target and flanking letters were of different order type. Our finding of substantial interaction between first- and second-order stimuli suggests that the processing of these stimuli is not independent at the stage of processing at which crowding occurs.