Biometric technologies are automated methods of verifying or recognizing. This work is particularly targeted towards the SURF,HARRIS and MSER calculations for biometric fingerprint calculations .These three features are used parallel to get the better identification results, FAR is proved 0 with the three algorithms and FRR is 1 with the same i.e. SURF, HARRIS and MSER and matching the maximum ...

This paper introduces a novel real-time framework which enables detection, tracking and recognition of license plates from video sequences. An efficient algorithm based on analysis of Maximally Stable Extremal Region (MSER) detection results allows localization of international license plates in single images without the need of any learning scheme. After a one-time detection of a plate it is r...

In this study, we investigate the effects of mandatory social and environmental regulations (MSER) on firm innovation. 2008, Shanghai Shenzhen Stock Exchange in China published that mandate some public firms to disclose their governance information annual reports. As MSER apply only selected firms, provides an ideal setting for us observe Using a difference-in-differences with propensity-score-...

This paper discusses an algorithm to build a semisupervised learning framework for detecting cells. The cell candidates are represented as extremal regions drawn from a hierarchical image representation. Training a classifier for cell detection using supervised approaches relies on a large amount of training data, which requires a lot of effort and time. We propose a semisupervised approach to ...

This thesis presents a robust online learning and recognition system. The basic idea is to exploit information from tracking an object during the recognition and/or learning stage to obtain increased robustness and better recognition results. Object tracking by means of an extended MSER tracker is utilized to extract local features and construct their trajectories. Compact object representation...

In this paper, a novel affine invariant descriptor for object matching is proposed. The advantage of Maximally Stable Extremal Regions (MSER) method is applied to get the most stable regions in the image. Inside each region, we pick the seeds as keypoints since MSER regions are invariant to affine transformation. Besides that, Voronoi diagram is employed to split the image into small Voronoi ce...