TY - GEN
T1 - Query-by-Example Word Spotting with Fuzzy Word Sizes
AU - Wiwatcharee, Amornchai
AU - Phienthrakul, Tanasanee
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - This paper proposed the query-by-example word spotting model for handwritten documents with image fuzzification. Fuzzy size of word images was used to size of problem. The number of classes in each set were decreased, which made it is easy to choose parameters. The Pyramid of Histogram of Oriented Gradients (PHOG) feature and Support Vector Machine (SVM) were employed to use in the model. IAM handwritten database was used for evaluating the model. The result demonstrates that the micro precision of model with image fuzzification and without image fuzzification were 35.11% and 23.54% respectively. However, the accuracies of the models were 35.11% and 40.14% respectively. Thus, the image fuzzification can be used for reducing of type one error with slightly accuracy loss.
AB - This paper proposed the query-by-example word spotting model for handwritten documents with image fuzzification. Fuzzy size of word images was used to size of problem. The number of classes in each set were decreased, which made it is easy to choose parameters. The Pyramid of Histogram of Oriented Gradients (PHOG) feature and Support Vector Machine (SVM) were employed to use in the model. IAM handwritten database was used for evaluating the model. The result demonstrates that the micro precision of model with image fuzzification and without image fuzzification were 35.11% and 23.54% respectively. However, the accuracies of the models were 35.11% and 40.14% respectively. Thus, the image fuzzification can be used for reducing of type one error with slightly accuracy loss.
KW - fuzzy logic
KW - handwritten recognition
KW - image fuzzification
KW - pyramid of histogram of oriented gradients
KW - query-by-example
KW - support vector machine
KW - word spotting
UR - https://www.scopus.com/pages/publications/85083593559
U2 - 10.1109/iSAI-NLP48611.2019.9045137
DO - 10.1109/iSAI-NLP48611.2019.9045137
M3 - Conference contribution
AN - SCOPUS:85083593559
T3 - Proceedings - 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2019
BT - Proceedings - 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2019
Y2 - 30 October 2019 through 1 November 2019
ER -