How to resolve the algorithm Hough transform step by step in the Rust programming language

Published on 12 May 2024 09:40 PM

How to resolve the algorithm Hough transform step by step in the Rust programming language

Table of Contents

Problem Statement

Implement the Hough transform, which is used as part of feature extraction with digital images. It is a tool that makes it far easier to identify straight lines in the source image, whatever their orientation. The transform maps each point in the target image,

( ρ , θ )

{\displaystyle (\rho ,\theta )}

, to the average color of the pixels on the corresponding line of the source image (in

( x , y )

{\displaystyle (x,y)}

-space, where the line corresponds to points of the form

x cos ⁡ θ + y sin ⁡ θ

ρ

{\displaystyle x\cos \theta +y\sin \theta =\rho }

). The idea is that where there is a straight line in the original image, it corresponds to a bright (or dark, depending on the color of the background field) spot; by applying a suitable filter to the results of the transform, it is possible to extract the locations of the lines in the original image. The target space actually uses polar coordinates, but is conventionally plotted on rectangular coordinates for display. There's no specification of exactly how to map polar coordinates to a flat surface for display, but a convenient method is to use one axis for

θ

{\displaystyle \theta }

and the other for

ρ

{\displaystyle \rho }

, with the center of the source image being the origin. There is also a spherical Hough transform, which is more suited to identifying planes in 3D data.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Hough transform step by step in the Rust programming language

Source code in the rust programming language

//! Contributed by Gavin Baker <gavinb@antonym.org>
//! Adapted from the Go version

use std::fs::File;
use std::io::{self, BufRead, BufReader, BufWriter, Read, Write};
use std::iter::repeat;

/// Simple 8-bit grayscale image
struct ImageGray8 {
    width: usize,
    height: usize,
    data: Vec<u8>,
}

fn load_pgm(filename: &str) -> io::Result<ImageGray8> {
    // Open file
    let mut file = BufReader::new(File::open(filename)?);

    // Read header
    let mut magic_in = String::new();
    let _ = file.read_line(&mut magic_in)?;
    let mut width_in = String::new();
    let _ = file.read_line(&mut width_in)?;
    let mut height_in = String::new();
    let _ = file.read_line(&mut height_in)?;
    let mut maxval_in = String::new();
    let _ = file.read_line(&mut maxval_in)?;

    assert_eq!(magic_in, "P5\n");
    assert_eq!(maxval_in, "255\n");

    // Parse header
    let width = width_in
        .trim()
        .parse::<usize>()
        .map_err(|_| io::ErrorKind::InvalidData)?;
    let height: usize = height_in
        .trim()
        .parse::<usize>()
        .map_err(|_| io::ErrorKind::InvalidData)?;

    println!("Reading pgm file {}: {} x {}", filename, width, height);

    // Create image and allocate buffer
    let mut img = ImageGray8 {
        width,
        height,
        data: vec![],
    };

    // Read image data
    let expected_bytes = width * height;
    let bytes_read = file.read_to_end(&mut img.data)?;
    if bytes_read != expected_bytes {
        let kind = if bytes_read < expected_bytes {
            io::ErrorKind::UnexpectedEof
        } else {
            io::ErrorKind::InvalidData
        };
        let msg = format!("expected {} bytes", expected_bytes);
        return Err(io::Error::new(kind, msg));
    }

    Ok(img)
}

fn save_pgm(img: &ImageGray8, filename: &str) {
    // Open file
    let mut file = BufWriter::new(File::create(filename).unwrap());

    // Write header
    if let Err(e) = writeln!(&mut file, "P5\n{}\n{}\n255", img.width, img.height) {
        println!("Failed to write header: {}", e);
    }

    println!(
        "Writing pgm file {}: {} x {}",
        filename, img.width, img.height
    );

    // Write binary image data
    if let Err(e) = file.write_all(&(img.data[..])) {
        println!("Failed to image data: {}", e);
    }
}

#[allow(clippy::cast_precision_loss)]
#[allow(clippy::clippy::cast_possible_truncation)]
fn hough(image: &ImageGray8, out_width: usize, out_height: usize) -> ImageGray8 {
    let in_width = image.width;
    let in_height = image.height;

    // Allocate accumulation buffer
    let out_height = ((out_height / 2) * 2) as usize;
    let mut accum = ImageGray8 {
        width: out_width,
        height: out_height,
        data: repeat(255).take(out_width * out_height).collect(),
    };

    // Transform extents
    let rmax = (in_width as f64).hypot(in_height as f64);
    let dr = rmax / (out_height / 2) as f64;
    let dth = std::f64::consts::PI / out_width as f64;

    // Process input image in raster order
    for y in 0..in_height {
        for x in 0..in_width {
            let in_idx = y * in_width + x;
            let col = image.data[in_idx];
            if col == 255 {
                continue;
            }

            // Project into rho,theta space
            for jtx in 0..out_width {
                let th = dth * (jtx as f64);
                let r = (x as f64) * (th.cos()) + (y as f64) * (th.sin());

                let iry = out_height as i64 / 2 - (r / (dr as f64) + 0.5).floor() as i64;
                #[allow(clippy::clippy::cast_sign_loss)]
                let out_idx = (jtx as i64 + iry * out_width as i64) as usize;
                let col = accum.data[out_idx];
                if col > 0 {
                    accum.data[out_idx] = col - 1;
                }
            }
        }
    }
    accum
}

fn main() -> io::Result<()> {
    let image = load_pgm("resources/Pentagon.pgm")?;
    let accum = hough(&image, 460, 360);
    save_pgm(&accum, "hough.pgm");
    Ok(())
}


  

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