Title :
Automatic recognition of symbols in utility maps
Author :
Manaf, Azizah Abdul ; Rijal, Omar Mohd ; Sulong, Ghazali
Author_Institution :
Fac. of Comp. Sci. & Inf., Malaya Univ., Kuala Lumpur, Malaysia
Abstract :
A new algorithm for matching and recognizing test symbols is developed via matching segments which identify the test symbol as one of the nearest prototypes. The measures of similarity between the segment lists involve (i) the total minimum cost and (ii) the Euclidean distance. The proportion of times a test image is correctly matched to the prototype is a measure of the probability of misclassification. Preliminary results using this technique show it to be quite promising, as a recognition rate of 80-90% has been achieved
Keywords :
CAD; cartography; feature extraction; image matching; nomenclature; probability; public utilities; Euclidean distance; automatic symbol recognition; feature extraction; misclassification probability; nearest prototype; recognition rate; segments; similarity measures; test symbol matching; total minimum cost; utility maps; Costs; Design automation; Euclidean distance; Image converters; Image segmentation; Manuals; Mathematics; Prototypes; Software prototyping; Testing;
Conference_Titel :
TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology. Proceedings of 1994
Print_ISBN :
0-7803-1862-5
DOI :
10.1109/TENCON.1994.369189
