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Biomedical subjects

M J Gervais

Publications and source records attributed to M J Gervais.

3 recordsLinked to original sources
PubMed1984

Identification confusions among letters of the alphabet.

Black, uppercase letters, subtending 6.0' of arc in height, were presented tachistoscopically to 6 subjects. An exposure duration was chosen to keep the subject's identification performance at about 50% correct. On each trial a single letter was presented, and the subject was required to identify the letter by verbal response. The resulting 26 X 26 confusion matrix was based on 3,900 trials (150 trials per letter). Several models of visual processing were used to generate predicted confusions among letter pairs. Models based on template overlap, geometric features, and two-dimensional spatial frequency content (Fourier transforms) were tested. The highest correlation (.70) between actual and predicted confusions was attained by the model based on the Fourier transformed letters filtered by the human contrast sensitivity function. These results demonstrate that the spatial frequency content of visual patterns can provide a valuable metric for predicting their psychological similarity. The results further suggest that spatial frequency models of visual processing are competitive with feature analysis models.

Discrimination, Psychological↗
PubMed1981

Internal representation of visual texture as the basis for the judgment of similarity.

The relationship between Fourier spectra of visual textures (represented both by the actual frequency components and by the response of four hypothetical channels selectively sensitive to spatial frequency) and the perceptual appearance of the textures was investigated. Thirty textures were synthesized by combining seven spatial frequencies whose amplitudes were randomly chosen and then scaled to give an overall contrast of .9. Similarity judgments were collected using both the method of triadic comparison (two subjects, 4,060 trials each) and the method of paired comparison (six subjects, 435 trials each). The similarity judgments were subjected to MDSCAL and INDSCAL dimensions were found to be optimally oriented in terms of spatial frequency information without rotation. The seven spatial frequency components accounted for 90.6% of the variance in the 3-D INDSCAL space, while the four channels accounted for 91.8% of the variance in the first two dimensions. The data further suggest that the four channels may interact in an opponent process manner. The results support the idea that the visual internal representation of stimuli is based on spatial frequency analysis rather than feature extraction.

Discrimination Learning↗