Text Localization in Video Using Multiscale Weber's Local Descriptor

In this paper, we propose a novel approach for detecting the text present in videos and scene images based on the Multiscale Weber's Local Descriptor (MWLD). Given an input video, the shots are identified and the key frames are extracted based on their spatio-temporal relationship. From each key frame, we detect the local region information using WLD with different radius and neighborhood relationship of pixel values and hence obtained intensity enhanced key frames at multiple scales. These multiscale WLD key frames are merged together and then the horizontal gradients are computed using morphological operations. The obtained results are then binarized and the false positives are eliminated based on geometrical properties. Finally, we employ connected component analysis and morphological dilation operation to determine the text regions that aids in text localization. The experimental results obtained on publicly available standard Hua, Horizontal-1 and Horizontal-2 video dataset illustrate that the proposed method can accurately detect and localize texts of various sizes, fonts and colors in videos.Comment: IEEE SPICES, 201

Word matching using single closed contours for indexing handwritten historical documents

Effective indexing is crucial for providing convenient access to scanned versions of large collections of historically valuable handwritten manuscripts. Since traditional handwriting recognizers based on optical character recognition (OCR) do not perform well on historical documents, recently a holistic word recognition approach has gained in popularity as an attractive and more straightforward solution (Lavrenko et al. in proc. document Image Analysis for Libraries (DIAL’04), pp. 278–287, 2004). Such techniques attempt to recognize words based on scalar and profile-based features extracted from whole word images. In this paper, we propose a new approach to holistic word recognition for historical handwritten manuscripts based on matching word contours instead of whole images or word profiles. The new method consists of robust extraction of closed word contours and the application of an elastic contour matching technique proposed originally for general shapes (Adamek and O’Connor in IEEE Trans Circuits Syst Video Technol 5:2004). We demonstrate that multiscale contour-based descriptors can effectively capture intrinsic word features avoiding any segmentation of words into smaller subunits. Our experiments show a recognition accuracy of 83%, which considerably exceeds the performance of other systems reported in the literature

Particle-by-Particle Reconstruction of Ultrafiltration Cakes in 3D from Binarized TEM Images

Transmission electron microscopy (TEM) imaging is one of the few techniques available for direct observation of the microstructure of ultrafiltration cakes. TEM images yield local microstructural information in the form of two-dimensional grayscale images of slices a few particle diameters in thickness. This work presents an innovative particle-by-particle reconstruction scheme for simulating ultrafiltration cake microstructure in three dimensions from TEM images. The scheme uses binarized TEM images, thereby permitting use of lesser-quality images. It is able to account for short- and long-range order within ultrafiltration cake structure by matching the morphology of simulated and measured microstructures at a number of resolutions and scales identifiable within the observed microstructure. In the end, simulated microstructures are intended for improving our understanding of the relationships between cake morphology, ultrafiltration performance, and operating conditions

Simulation of 3D granular media by multiscale random polyhedra

International audienceIn order to simulate granular microstructures such as cementitious materials, a Boolean Poisson polyhedra model is implemented. 3D images are generated as vector images for derivation of faster algorithms. Different morphological measurements (specifically covariance of mosaic and Boolean models, and geometrical covariogram of primary grains), which theoretical expressions are known for such models, are used to validate the algorithm