Progressive Probabilistic Hough Transform for line detection

We present a novel Hough Transform algorithm referred to as Progressive Probabilistic Hough Transform (PPHT). Unlike the Probabilistic HT where Standard HT is performed on a pre-selected fraction of input points, PPHT minimises the amount of computation needed to detect lines by exploiting the difference an the fraction of votes needed to detect reliably lines with different numbers of supporting points. The fraction of points used for voting need not be specified ad hoc or using a priori knowledge, as in the probabilistic HT; it is a function of the inherent complexity of the input data. The algorithm is ideally suited for real-time applications with a fixed amount of available processing time, since voting and line detection is interleaved. The most salient features are likely to be detected first. Experiments show that in many circumstances PPHT has advantages over the Standard HT

Text Detection In Indonesian Identity Card Based On Maximally Stable Extremal Regions

Most of Indonesian organizations either it is government or non government sometime required their member to provide their identity card (E-KTP) as legal document collection in their database. This collection of image usually being used as manual verification method. These document images acquired by each person with their own device, there are variations of angles they are used to acquire the image. This situation created problems in text recognition by OCR softwares especially in text detection part, orientation and noise will affect their accuracy. These cases making the text detection more complex and cannot be solved by simple vertical projection profile of black pixels.  This research proposed a method to improve text detection in identity document by fixing the orientation first, then using MSER regions to form text region. We fix the orientation using the line that made by Progressive Probabilistic Hough Transform. Then we used MSER to obtain all candidate regions and Horizontal RLSA acts as connector between those candidate. The orientation fixing strategy reach average of margin error 0.377o (in 360o system) and the text detection method reach 84.49% accuracy in best condition

Automated Generation of Geometric Theorems from Images of Diagrams

We propose an approach to generate geometric theorems from electronic images of diagrams automatically. The approach makes use of techniques of Hough transform to recognize geometric objects and their labels and of numeric verification to mine basic geometric relations. Candidate propositions are generated from the retrieved information by using six strategies and geometric theorems are obtained from the candidates via algebraic computation. Experiments with a preliminary implementation illustrate the effectiveness and efficiency of the proposed approach for generating nontrivial theorems from images of diagrams. This work demonstrates the feasibility of automated discovery of profound geometric knowledge from simple image data and has potential applications in geometric knowledge management and education.Comment: 31 pages. Submitted to Annals of Mathematics and Artificial Intelligence (special issue on Geometric Reasoning

The DECam Ecliptic Exploration Project (DEEP) IV: Constraints on the shape distribution of bright TNOs

We present the methods and results from the discovery and photometric measurement of 26 bright (VR $>$ 24 trans-Neptunian objects (TNOs) during the first year (2019-20) of the DECam Ecliptic Exploration Project (DEEP). The DEEP survey is an observational TNO survey with wide sky coverage, high sensitivity, and a fast photometric cadence. We apply a computer vision technique known as a progressive probabilistic Hough transform to identify linearly-moving transient sources within DEEP photometric catalogs. After subsequent visual vetting, we provide a photometric and astrometric catalog of our TNOs. By modeling the partial lightcurve amplitude distribution of the DEEP TNOs using Monte Carlo techniques, we find our data to be most consistent with an average TNO axis ratio b/a $<$ 0.5, implying a population dominated by non-spherical objects. Based on ellipsoidal gravitational stability arguments, we find our data to be consistent with a TNO population containing a high fraction of contact binaries or other extremely non-spherical objects. We also discuss our data as evidence that the expected binarity fraction of TNOs may be size-dependent

Повышение эффективности обобщенного 3D преобразования Хафа

В данной работе продолжены исследования, связанные с повышением эффективности обобщённого преобразования Хафа для поиска нескольких сферических поверхностей по заданному трехмерному массиву точек в пространстве. Предложен способ распараллеливания работы алгоритма для ускорения его работы на многоядерных персональных компьютерах. Наибольшую эффективность данный поход показывает вместе с каскадным преобразованием

A Study on Software-based Sensing Technology for Multiple Object Control in AR Video

Researches on Augmented Reality (AR) have recently received attention. With these, the Machine-to-Machine (M2M) market has started to be active and there are numerous efforts to apply this to real life in all sectors of society. To date, the M2M market has applied the existing marker-based AR technology in entertainment, business and other industries. With the existing marker-based AR technology, a designated object can only be loaded on the screen from one marker and a marker has to be added to load on the screen the same object again. This situation creates a problem where the relevant marker’should be extracted and printed in screen so that loading of the multiple objects is enabled. However, since the distance between markers will not be measured in the process of detecting and copying markers, the markers can be overlapped and thus the objects would not be augmented. To solve this problem, a circle having the longest radius needs to be created from a focal point of a marker to be copied, so that no object is copied within the confines of the circle. In this paper, software-based sensing technology for multiple object detection and loading using PPHT has been developed and overlapping marker control according to multiple object control has been studied using the Bresenham and Mean Shift algorithms

Feature Extraction Using the Hough Transform

This paper contains a brief literature survey of applications and improvements of the Hough transform, a description of the Hough transform and a few of its algorithms, and simulation examples of line and curve detection using the Hough transform