A computer-controlled color vision test for children based on the Cambridge Colour Test

The present study aimed at providing conditions for the assessment of color discrimination in children using a modified version of the Cambridge Colour Test (CCT, Cambridge Research Systems Ltd., Rochester, UK). Since the task of indicating the gap of the Landolt C used in that test proved counterintuitive and/or difficult for young children to understand, we changed the target Stimulus to a patch of color approximately the size of the Landolt C gap (about 7 degrees Of Visual angle at 50 cm from the monitor). The modifications were performed for the CCT Trivector test which measures color discrimination for the protan, deutan and tritan confusion lines. Experiment I Sought to evaluate the correspondence between the CCT and the child-friendly adaptation with adult subjects (n = 29) with normal color vision. Results showed good agreement between the two test versions. Experiment 2 tested the child-friendly software with children 2 to 7 years old (n = 25) using operant training techniques for establishing and maintaining the subjects` performance. Color discrimination thresholds were progressively lower as age increased within the age range tested (2 to 30 years old), and the data-including those obtained for children-fell within the range of thresholds previously obtained for adults with the CCT. The protan and deutan thresholds were consistently lower than tritan thresholds, a pattern repeatedly observed in adults tested with the CCT. The results demonstrate that the test is fit for assessment of color discrimination in young children and may be a useful tool for the establishment of color vision thresholds during development.

Using the Hard, Randy, and Rittler Test to Evaluate Color Vision in Capuchins (Cebus libidinosus)

The identification of color vision types in primates is fundamental to understanding the evolution and biological function of color perception. The Hard, Randy, and Rittler (HRR) pseudoisochromatic test categorizes human color vision types successfully. Here we provide an experimental setup to employ HRR in a nonhuman primate, the capuchin (Cebus libidinosus), a platyrrhine with polymorphic color vision. The HRR test consists of plates with a matrix composed of gray circles that vary in size and brightness. Differently colored circles form a geometric shape (X, O, or Delta) that is discriminated visually from the gray background pattern. The ability to identify these shapes determines the type of dyschromatopsy (deficiency in color vision). We tested six capuchins in their own cages under natural sunlight. The subjects chose between two HRR plates in each trial: one with the gray pattern only and the other with a colored shape, presented on the left or right side at random. We presented the test 40 times and calculated the 95 % confidence limits for chance performance based on the binomial test. We also genotyped all subjects for exons 3 and 5 of the X-linked opsin genes. The HRR test diagnosed two subjects as protan dichromats (missing or defective L-cone), three as deutan dichromats (missing or defective M-cone), and one female as trichromat. Genetic analysis supported the behavioral data for all subjects. These findings show that the HRR test can be applied to diagnose color vision in nonhuman primates.

Texture descriptor based on partially self-avoiding deterministic walker on networks

Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

Optical aids for low vision: use of the Internet to guide teachers of the visually impaired

PURPOSES: To describe and interpret teachers' opinions about and responsiveness to guidance on optical aids for low vision. METHODS: It was conducted a cross-sectional analytical study. The convenience, non-random sample consisted of 58 teachers from the public school network of the city of Campinas. It was constructed and applied a structured questionnaire, available online at the assessed website. For qualitative data collection it was conducted an exploratory study using the focus group technique. RESULTS: Responses expressed, for the most part, a marked interest in the website, its easiness of access, and the comprehensive nature of the information provided. Most people reported frequent use of the Internet to seek information, and found it easier to access the Internet at home. Among the qualitative aspects of the evaluation, we should mention the perceived importance of the website as a source of information, despite some criticism about the accessibility and reliability of the information found on the Internet. CONCLUSION: Teachers' need for training to deal with visually impaired students and their positive response to advice and information lead to the conclusion that web-based guidelines on the use of optical aids were considered beneficial to ease the understanding of visual impairment and the rehabilitation of the affected subjects.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.