New texture-spatial features for keyword spotting in video images
Document Type
Conference Article
Publication Title
Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015
Abstract
Keyword spotting in video document images is challenging due to low resolution and complex background of video images. We propose the combination of Texture-Spatial-Features (TSF) for keyword spotting in video images without recognizing them. First, a segmentation method extracts words from text lines in each video image. Then we propose the set of texture features for identifying text candidates in the word image with the help of k-means clustering. The proposed method finds proximity between text candidates to study the spatial arrangement of pixels that result in feature vectors for spotting words in the input frame. The proposed method is evaluated on word images of different fonts, contrasts, backgrounds and font sizes, which are chosen from standard databases such as ICDAR 2013 video and our video data. Experimental results show that the proposed method outperforms the existing method in terms of recall, precision and f-measure.
First Page
391
Last Page
395
DOI
10.1109/ACPR.2015.7486532
Publication Date
6-7-2016
Recommended Citation
Shivakumara, Palaiahnakote; Liang, Guozhu; Roy, Sangheeta; Pal, Umapada; and Lu, Tong, "New texture-spatial features for keyword spotting in video images" (2016). Conference Articles. 760.
https://digitalcommons.isical.ac.in/conf-articles/760
