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Large-scale digitisation of historical documents demands robust methods that cope with the presence of frequent distortions and noisy artefacts. This paper presents a hybrid text line segmentation method that uses a novel data structure and a rule base to combine the strengths of top-down and bottom-up approaches while minimising their weaknesses. The effectiveness of the proposed approach has been...
This paper investigates the segmentation of multiple planar surfaces from 3D point clouds. A Principle Component Analysis (PCA) based covariance technique is used for segmentation which is one of the most popular approaches in point cloud processing. It is well known that PCA is very sensitive to outliers and does not give reliable estimates for segmentation. We propose a statistically robust segmentation...
This paper presents a robust fuzzy clustering algorithm which can perform clustering without pre-assigning the number of clusters and is not sensitive to the initialization of cluster centers. This is achieved by iteratively splitting and merging operations under the guidance of mistake measurements. In every step of the iteration, we first split the cluster containing data points belonging to different...
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