ARTICLE odobez-ijprai05/IDIAP Monte Carlo Video Text Segmentation Chen, Datong Odobez, Jean-Marc Thiran, Jean-Philippe EXTERNAL https://publications.idiap.ch/attachments/reports/2005/odobez_ijprai_2005.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/chen-rr0343 Related documents International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI) 19 5 647-661 2005 August 2005 IDIAP-RR 03-43 This paper presents a probabilistic algorithm for segmenting and recognizing text embedded in video sequences based on adaptive thresholding using a Bayes filtering method. The algorithm approximates the posterior distribution of segmentation thresholds of video text by a set of weighted samples. The set of samples is initialized by applying a classical segmentation algorithm on the first video frame and further refined by random sampling under a temporal Bayesian framework. This framework allows us to evaluate an text image segmentor on the basis of recognition result instead of visual segmentation result, which is directly relevant to our character recognition task. Results on a database of 6944 images demonstrate the validity of the algorithm. REPORT chen-rr0343/IDIAP Video Text Segmentation Using Particle Filters Chen, Datong Odobez, Jean-Marc EXTERNAL https://publications.idiap.ch/attachments/reports/2003/rr03-43.pdf PUBLIC Idiap-RR-43-2003 2003 IDIAP May 2003 published in Int. Journal of Pattern Recognition and Artificial Intelligence This paper presents a probabilistic algorithm for segmenting and recognizing text embedded in video sequences based on adaptive thresholding using a Bayes filtering method. The algorithm approximates the posterior distribution of segmentation thresholds of video text by a set of weighted samples. The set of samples is initialized by applying a classical segmentation algorithm on the first video frame and further refined by random sampling under a temporal Bayesian framework. This framework allows us to evaluate an text image segmentor on the basis of recognition result instead of visual segmentation result, which is directly relevant to our character recognition task. Results on a database of 6944 images demonstrate the validity of the algorithm.