Form processing with the Hough transform

A form document processing system based on the Hough transform (HT) is developed. It performs form identification and form registration. For form identification, HT is applied off-line to master forms to calculate form features and build-up the feature database, and it is performed on-line for the input (scanned) forms to extract features to identify the form type based on feature matching. The derived features are rotation, translation and scale invariant. The proposed form description is compact, thereby allows for fast identification. The registration is feature/knowledge based. Two methods for control points detection are discussed; one implements template matching for finding frame corners. The second approach is based on detection of line crossings via the analysis of the parameter space of the HT. Detected control points are used to calculate parameters of geometrical transform and perform coordinates translation. Linear conformal and projective transforms are tested. The system is featured by fast and reliable type identification, and the moderate preprocessing time, which is attained by proper design of the Hough space

Vanishing Point Detection with Direct and Transposed Fast Hough Transform inside the neural network

In this paper, we suggest a new neural network architecture for vanishing point detection in images. The key element is the use of the direct and transposed Fast Hough Transforms separated by convolutional layer blocks with standard activation functions. It allows us to get the answer in the coordinates of the input image at the output of the network and thus to calculate the coordinates of the vanishing point by simply selecting the maximum. Besides, it was proved that calculation of the transposed Fast Hough Transform can be performed using the direct one. The use of integral operators enables the neural network to rely on global rectilinear features in the image, and so it is ideal for detecting vanishing points. To demonstrate the effectiveness of the proposed architecture, we use a set of images from a DVR and show its superiority over existing methods. Note, in addition, that the proposed neural network architecture essentially repeats the process of direct and back projection used, for example, in computed tomography.Comment: 9 pages, 9 figures, submitted to "Computer Optics"; extra experiment added, new theorem proof added, references added; typos correcte

Cleaning sky survey databases using Hough Transform and Renewal String approaches

Large astronomical databases obtained from sky surveys such as the SuperCOSMOS Sky Survey (SSS) invariably suffer from spurious records coming from artefactual effects of the telescope, satellites and junk objects in orbit around earth and physical defects on the photographic plate or CCD. Though relatively small in number these spurious records present a significant problem in many situations where they can become a large proportion of the records potentially of interest to a given astronomer. Accurate and robust techniques are needed for locating and flagging such spurious objects, and we are undertaking a programme investigating the use of machine learning techniques in this context. In this paper we focus on the four most common causes of unwanted records in the SSS: satellite or aeroplane tracks, scratches, fibres and other linear phenomena introduced to the plate, circular halos around bright stars due to internal reflections within the telescope and diffraction spikes near to bright stars. Appropriate techniques are developed for the detection of each of these. The methods are applied to the SSS data to develop a dataset of spurious object detections, along with confidence measures, which can allow these unwanted data to be removed from consideration. These methods are general and can be adapted to other astronomical survey data.Comment: Accepted for MNRAS. 17 pages, latex2e, uses mn2e.bst, mn2e.cls, md706.bbl, shortbold.sty (all included). All figures included here as low resolution jpegs. A version of this paper including the figures can be downloaded from http://www.anc.ed.ac.uk/~amos/publications.html and more details on this project can be found at http://www.anc.ed.ac.uk/~amos/sattrackres.htm

About the directional properties of Solar Spicules from Hough Transform analysis

Spicules are intermittently rising above the surface of the Sun eruptions; EUV jets are now also reported in immediately above layers. The variation of spicule orientation with respect to the solar latitude, presumably reflecting the confinement and the focusing of ejecta by the surrounding global coronal magnetic field, is an important parameter to understand their dynamical properties. A wealth of high resolution images of limb spicules are made available in H CaII emission from the SOT Hinode mission. Furthermore, the Hough transform is applied to the resulting images for making a statistical analysis of spicule orientations in different regions around the solar limb, from the pole to the equator. Results show a large difference of spicule apparent tilt angles in: (i) the solar pole regions, (ii) the equatorial regions, (iii) the active regions and (iv) the coronal hole regions. Spicules are visible in a radial direction in the polar regions with a tilt angle (less than 200). The tilt angle is even reduced to 10 degrees inside the coronal hole with open magnetic field lines and at the lower latitude the tilt angle reaches values in excess of 50 degree. Usually, which is in close resemblance to the rosettes made of dark mottles and fibrils in projection on the solar disk. The inference of these results for explaining the so-called chromospheric prolateness observed at solar minimum of activity in cool chromospheric lines is considered.Comment: 13 pages, 6 figure