Text spotting is an interesting research problem as text may appear at any random place and may occur in various forms. Moreover, ability to detect text opens the horizons for improving many advanced computer vision problems. In this paper, we propose a novel language agnostic text detection method utilizing edge enhanced Maximally Stable Extremal Regions in natural scenes by defining strong ch...

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...

Methods for generating maximally stable extremal regions are generalised to make intensity trees. Such trees may be computed quickly, but they are large so there is a need to select useful nodes within the tree. Methods for simplifying the tree are developed and it is shown that standard confidence tests may be applied to regions identified as parent and child nodes in the tree. These tests pro...

This paper proposes a system that detects and recognizes speed-limit signs automatically. The system detects potential speed-limit sign regions by detecting maximally stable extremal regions (MSERs). The recognition is achieved by using a Support Vector Machine (SVM) classifier. The proposed system provides robustness and high accuracy in detecting and recognizing speed-limit signs when input i...

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...

In this paper we present a new algorithm for computing Maximally Stable Extremal Regions (MSER), as invented by Matas et al. The standard algorithm makes use of a union-find data structure and takes quasi-linear time in the number of pixels. The new algorithm provides exactly identical results in true worst-case linear time. Moreover, the new algorithm uses significantly less memory and has bet...

The manual Chinese word segmentation dataset WordSegCHC 1.0 which was built by eight crowdsourcing tasks conducted on the Crowdflower platform contains the manual word segmentation data of 152 Chinese sentences whose length ranges from 20 to 46 characters without punctuations. All the sentences received 200 segmentation responses in their corresponding crowdsourcing tasks and the numbers of val...

This work 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 detect local features and construct their trajectories. Compact object representations a...

In a comprehensive study of methods for dealing with the problem of the initial transient, Hoad et al. (2008) determined that the MSER (White, 1997) was an efficient and effective truncation rule appropriate for automation. In this paper, we suggest that the MSER works well because it minimizes an approximation to the mean-squared error in the estimated steady-state mean. Using the example of a...