Chinese character recognition : studies of complexity effect on recognition efficiency, spatial frequency characteristics, crowding and expertise

Abstract

Chinese characters are used by about one-fifth of the world population. Each character can generally be analyzed and represented at three orthographic levels including single stroke, component and whole character. Regardless of the number of strokes a Chinese character has, it always occupies a square area. Such special spatial layout leads to a great variation in stroke density, i.e., visual complexity, among Chinese characters. Here in this thesis, the effects of visual complexity on Chinese character recognition were examined to investigate the visual processing of Chinese characters in both central and peripheral vision.

Empirical findings from four psychophysical studies will be reported. First, the efficiency of detecting and recognizing Chinese characters of different complexity levels was studied. Human recognition of a more complex Chinese character was found to be generally less efficient than that of a simpler one. The relationship between efficiency and complexity had a log-log slope of approximately -1, suggesting that the basic features for recognizing a single Chinese character might be less complex than the simplest object used, which is a single stroke. Analysis results of the detection and recognition efficiency were consistent with a two-stage processing model of Chinese character recognition—feature detection followed by feature integration. Results in peripheral vision suggested that the feature integration process was adversely influenced by internal crowding.

Second, the spatial frequency characteristics of recognizing Chinese characters of different complexity levels were examined. The results showed that the peak tuning frequency for recognizing a more complex Chinese character was higher and the bandwidth of the spatial tuning functions was narrower than for recognizing a simpler character. In addition, the effects of size on such spatial frequency characteristics depended on the complexity level. The comparison of human performance against the corresponding performance of a CSF-limited ideal observer model implied that the processing mechanism of recognizing simple and complex characters was different. Moreover, similar results were observed among native Chinese and non-Chinese readers, suggesting that expertise might not influence front end processing properties such as the spatial frequency characteristics of Chinese character recognition.

Third, the importance of utilizing spatial frequency information of different orientations (i.e., horizontal versus vertical) in Chinese character recognition was investigated. Results showed higher efficiency in utilizing vertical than horizontal stroke information for Chinese character recognition among native Chinese readers whereas non-Chinese readers used both vertical and horizontal stroke information similarly. Fourth, the effects of the target-flanker similarity in complexity on crowding in Chinese character recognition were examined. The results suggested that the behavior of feature integration process in peripheral vision might be consistent with summation theory, which stresses on the relationship between the processing capacity of neurons and the processing demand of stimuli. The “excessive feature integration explanation” of crowding was also discussed in the context of the current findings.

Building on previous research in the literature, results from the four studies in this thesis were synthesized in a proposal of a visual information processing model for Chinese character recognition.