scholarly journals The effect of letter string length and report condition on letter recognition accuracy

2017 ◽  
Vol 10 (3) ◽  
pp. 176-188
Author(s):  
Avesh Raghunandan ◽  
Berta Karmazinaite ◽  
Andrea S. Rossow
1987 ◽  
Vol 42 (5) ◽  
pp. 503-509 ◽  
Author(s):  
A. H. C. Van Der Heijden ◽  
G. Wolters ◽  
J. C. Groep ◽  
R. Hagenaar

2012 ◽  
Vol 74 (7) ◽  
pp. 1533-1538 ◽  
Author(s):  
Jos J. Adam ◽  
Thamar J. H. Bovend’Eerdt ◽  
Fleur E. P. van Dooren ◽  
Martin H. Fischer ◽  
Jay Pratt

2003 ◽  
Vol 15 (7) ◽  
pp. 1052-1062 ◽  
Author(s):  
T. N. Wydell ◽  
T. Vuorinen ◽  
P. Helenius ◽  
R. Salmelin

Behavioral studies have shown that short letter strings are read faster than long letter-strings and words are read faster than nonwords. Here, we describe the dynamics of letter-string length and lexicality effects at the cortical level, using magnetoencephalography, during a reading task in Finnish with long (eight-letter) and short (four-letter) word/nonword stimuli. Length effects were observed in two spatially and temporally distinct cortical activations: (1) in the occipital cortex at about 100 msec by the strength of activation, regardless of the lexical status of the stimuli, and (2) in the left superior temporal cortex between 200 and 600 msec by the duration of activation, with words showing a smaller effect than nonwords. A significant lexicality effect was also evident in this later activation, with stronger activation and longer duration for nonwords than words. There seem to be no distinct cortical areas for reading words and nonwords. The early length effect is likely to be due to the low-level visual analysis common to all stimulus letter-strings. The later lexicality and length effects apparently reflect converging lexico-semantic and phonological influences, and are discussed in terms of dual-route and single-route connectionist models of reading.


1979 ◽  
Vol 49 (1) ◽  
pp. 183-191
Author(s):  
Colin Pitblado ◽  
Michael Petrides ◽  
Gary Riccio

Two experiments on visual-field differences in tachistoscopic letter recognition are described. In the first, a bright pre-exposure field with a black fixation point was used, and the conventionally expected dominance of the right visual field was found. However, a large number of “blank” trials were observed, in which subjects completely failed to detect the presence of the flashed target. These “blanks” were themselves significantly asymmetric between visual fields, suggesting that asymmetry in early stimulus registration may play an unsuspected role in typical measures of cerebral asymmetry in recognition accuracy. This was confirmed in a second experiment in which use of dark pre-exposure fields eliminated “blanks” and led to higher over-all accuracy, with no visual-field differences. Implications for interpretation of laterality data with normal subjects are discussed.


1992 ◽  
Vol 30 (2) ◽  
pp. 101-104 ◽  
Author(s):  
A. H. C. Van Der Heijden ◽  
G. Wolters ◽  
E. Fleur ◽  
J. G. M. Hommels

1992 ◽  
Vol 54 (3) ◽  
pp. 182-186
Author(s):  
A. H. C. van der Heijden ◽  
R. F. T. Brouwer ◽  
A. W. Serbe

2017 ◽  
Vol 4 (1) ◽  
pp. 66-75
Author(s):  
Maulidia Rahmah Hidayah ◽  
Isa Akhlis ◽  
Endang Sugiharti

The current topic that is interesting as a solution of the impact of public service improvement toward vehicle is License Plate Recognition (LPR), but it still needs to develop the research of LPR method. Some of the previous researchs showed that K-Nearest Neighbour (KNN) succeed in car license plate recognition. The Objectives of this research was to determine the implementation and accuracy of Otsu Method toward license plate recognition. The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. The study showed that this program can recognize by 82% from 100 test plate with 93,75% of number recognition accuracy and 91,92% of letter recognition accuracy.


NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 628
Author(s):  
Taeko Wydell ◽  
Tiina Vuorinent ◽  
Paivi Helenius ◽  
Ruffs Salmelin

1982 ◽  
Vol 55 (2) ◽  
pp. 343-349 ◽  
Author(s):  
Yutaka Shimizu

Two experiments examined the temporal effect on tactile letter recognition of sequentially tracing a stimulus in the order of making the necessary strokes. The effect of time interval between letter-strokes was examined in Exp. 1, with the three measures, recognition accuracy, latency, and readability. Accuracy of recognition did not differ by change in time intervals, but latency showed a downward trend, and readability showed an upward trend with an increase in the time interval. The effect of duration of exposure (number of pulses which activates each vibratory stimulator defining a letter) was examined in Exp. II with two measures, accuracy of recognition and latency. Both accuracy of recognition and latency reached optimum with 8 pulses per stimulator. The time interval between letter-strokes contributed strongly at the shorter exposure. The minimum was about 80 msec, for the interval between letter-strokes, and 4 pulses per stimulator considering the practical demands of fast exposure and easy identification.


2017 ◽  
Author(s):  
Hélène Manning ◽  
FranÇois Tremblay

Young (21-26 years, n=20) and Old (55-86 years, n=25) participants were tested for their ability to recognize raised letters (6-mm high, 1-mm relief) by touch. Spatial resolution thresholds were also measured with grating domes to derive an index of the degree of afferent innervation at the fingertip. Letter recognition in the young group was very consistent and highly accurate (mean, 86% correct), contrasting with the performance of the old group, which was more variable and comparatively low in accuracy (mean, 53% correct). In both groups, spatial resolution thresholds accounted for a substantial portion of the variance in the performance, suggesting a strong link between age-dependant variations in tactile innervation and recognition accuracy. The patterns of errors in the old group showed that an inability to encode internal elements specific to certain letters was at the source of most confusion among letters. Whether this inability reflected only deficient peripheral encoding mechanisms or some other alterations at the central level is discussed.


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