Simulated Hough Transform Model Optimized for Straight-Line Recognition Using Frontier FPGA Devices

Abstract

The use of the Hough transforms to identify shapes or images has been extensively studied in the past using software for artificial intelligence applications. In this article, we present a generalization of the goal of shape recognition using the Hough transform, applied to a broader range of real problems. A software simulator was developed to generate input patterns (straight-lines) and test the ability of a generic low-latency system to identify these lines: first in a clean environment with no other inputs and then looking for the same lines as ambient background noise increases. In particular, the paper presents a study to optimize the implementation of the Hough transform algorithm in programmable digital devices, such as FPGAs. We investigated the ability of the Hough transform to discriminate straight-lines within a vast bundle of random lines, emulating a noisy environment. In more detail, the study follows an extensive investigation we recently conducted to recognize tracks of ionizing particles in high-energy physics. In this field, the lines can represent the trajectories of particles that must be immediately recognized as they are created in a particle detector. The main advantage of using FPGAs over any other component is their speed and low latency to investigate pattern recognition problems in a noisy environment. In fact, FPGAs guarantee a latency that increases linearly with the incoming data, while other solutions increase latency times more quickly. Furthermore, HT inherently adapts to incomplete input data sets, especially if resolutions are limited. Hence, an FPGA system that implements HT is inefficient for small sets of input data but becomes more cost-effective as the size of the input data increases. The document first presents an example that uses a large Accumulator consisting of 1100 × 600 Bins and several sets of input data to validate the Hough transform algorithm as random noise increases to 80% of input data. Then, a more specifically dedicated input set was chosen to emulate a real situation where a Xilinx UltraScale+ was to be used as the final target device. Thus, we have reduced the Accumulator to 280 × 280 Bins using a clock signal at 250 MHz and a few tens input points. Under these conditions, the behavior of the firmware matched the software simulations, confirming the feasibility of the HT implementation on FPGA.

Development of a two-stage method for segmenting the color images of urban terrain acquired from space optic-electronic observation systems based on the ant algorithm and the hough algorithm

“…At the second stage of the method of segmenting images of urbanized areas, we shall use the Hough algorithm for straight lines [29,36,37]. The essence of Hough algorithm is to use the voting procedure to the parameter space of each of the figures, from which such simple figures in an accumulative space can be obtained at local maxima.…”

“…where ρ is the length of the perpendicular made from the beginning of the coordinates (0; 0) on the straight line; α is the angle between ρ and the x axis a straight line is set on the plane [29,36,37]. Many straight lines can be drawn through one point of the Cartesian plane.…”

Hough Transform Proposal and Simulations for Particle Track Recognition for LHC Phase-II Upgrade

“…Recently, the HT algorithm has been studied and implemented on many electronic cards [8][9][10][11]. In particular, in this study we show the algorithm investigated for tracking detectors in HEPE, where it is used to extract trajectories and straight or curved lines, within digital image representations of the particle space.…”

“…Formula (1) executes the conversion from the particle space to the HS using (r) as the radius of the detector layer in the real transversal plane, (ϕ) as the angle of the Hit with respect to the horizontal axis; let us say that these are the input parameters. On the contrary, (φ 0 ) is the same angle of the particle trajectory with respect the origin, and let us call it an output parameter of Formula (1), along with the ( Aq Pt ), which is described below (see [8,9] for details). Formula (1) computes, for each pair of Hits, many operations by varying (φ 0 ) angles and, consequently, any Hit in the parameter space creates many straight-lines in the HS.…”

“…If more Roads are generated, these will be eliminated by a further cross-check using additional layers than those used in the HT process. In [8,9], we report a hardware implementation, with the detail of the block diagram, while in this paper we broaden the field to generic low latency applications, and this is why we have designed a software development tool. Compared to other similar devices [19][20][21], FPGA components can simultaneously provide low and fixed latency, low power budget, and high data rate.…”