image-js/lib/featureMatching/utils/getGaussianPoints.js

Image processing and manipulation in JavaScript

import { createRandomArray } from 'ml-spectra-processing';
import { getClampFromTo } from '../../utils/clamp.js';
/**
 * Get the coordinates of random points inside of the given dimensions, spread with a
 * gaussian distribution around the center of the dimensions.
 * The reference point with coordinates (0,0) is the center of the patch.
 * @param width - Width in which the points should be.
 * @param height - Height in which the points should be.
 * @param options - Get gaussian points options.
 * @returns An array of random points with a gaussian distribution.
 */
export function getGaussianPoints(width, height, options = {}) {
    const { nbPoints = 1024, xSeed = 0, ySeed = 1, sigma } = options;
    const xCoordinates = getGaussianValues(width, xSeed, nbPoints, sigma);
    const yCoordinates = getGaussianValues(height, ySeed, nbPoints, sigma);
    const points = [];
    for (let i = 0; i < nbPoints; i++) {
        points.push({ column: xCoordinates[i], row: yCoordinates[i] });
    }
    return points;
}
/**
 * Generate an array of values
 * that follow a gaussian distribution with a mean value of zero.
 * @param size - Specifies the width of the gaussian distribution.
 * @param seed - Seed for the random generator.
 * @param nbValues - Number of values wanted.
 * @param sigma - The standard deviation. The default value is the optimal SD for BRIEF.
 * @returns Array of values with gaussian distribution.
 */
export function getGaussianValues(size, seed, nbValues, sigma = size / 5) {
    const width = (size - 1) / 2;
    const array = createRandomArray({
        distribution: 'normal',
        seed,
        length: nbValues,
        standardDeviation: sigma,
        mean: 0,
    });
    const clamp = getClampFromTo(-width, width);
    return array.map((value) => {
        const rounded = Math.round(value);
        return clamp(rounded);
    });
}
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