images4/README.md

Find similar images with Go (LATEST VERSION)

Resized images and near duplicates can be found with the package. No dependencies.

Demo: similar pictures search and clustering (deployed from).

Semantic versions:

• v4 (/images4) - this repository, latest recommended,
• v3 (/images3),
• v1/v2 (/images).

All versions will be kept available indefinitely.

Release note (v4): simplified func Icon; more than 2x reduction of icon memory footprint; removal of all dependencies; removal of hashes (a separate new package imagehash can be used for fast large scale preliminary search); fixed GIF support; new func IconNN. The main improvements in v4 are package simplification and memory footprint reduction.

Main functions

• Open supports JPEG, PNG and GIF. But other image types can be used through third-party decoders, because input for func Icon is Golang image.Image.

• Icon produces "image hashes" called "icons", which will be used for comparision.

• Similar gives a verdict whether 2 images are similar with well-tested default thresholds. To see the thresholds use DefaultThresholds. Rotations and mirrors are not taken in account.

• Similar90270 is a superset of Similar by additional comparison to images rotated ±90°. Such rotations are relatively common, even by accident when taking pictures on mobile phones.

• EucMetric can be used instead of Similar when you need different precision or want to sort by similarity. Example (not mine).

• PropMetric allows customization of image proportion threshold.

• DefaultThresholds prints default thresholds used in func Similar and Similar90270, as a starting point for selecting thresholds on EucMetric and PropMetric.

• Rotate90 turns an icon 90° clockwise. This is useful for developing custom similarity function for rotated images with EucMetric and PropMetric. With the function you can also compare to images rotated 180° (by applying Rotate90 twice).

Go doc for code reference.

Example of comparing 2 images

package main

import (
	"fmt"
	"github.com/vitali-fedulov/images4"
)

func main() {

	// Photos to compare.
	path1 := "1.jpg"
	path2 := "2.jpg"

	// Open files (discarding errors here).
	img1, _ := images4.Open(path1)
	img2, _ := images4.Open(path2)

	// Icons are compact image representations (image "hashes").
	// Name "hash" is reserved for hash tables (in package imagehash).
	icon1 := images4.Icon(img1)
	icon2 := images4.Icon(img2)

	// Comparison.
	// Images are not used directly. Icons are used instead,
	// because they have tiny memory footprint and fast to compare.
	// Use func Similar90270 to include images rotated right and left.
	if images4.Similar(icon1, icon2) {
		fmt.Println("Images are similar.")
	} else {
		fmt.Println("Images are distinct.")
	}
}

Algorithm

Detailed explanation, also as a PDF.

Summary: Images are resized in a special way to squares of fixed size called "icons". Euclidean distance between the icons is used to give the similarity verdict. Also image proportions are used to avoid matching images of distinct shape.

Customization suggestions

To increase precision you can either use your own thresholds in func EucMetric (and PropMetric) OR generate icons for image sub-regions and compare those icons.

To speedup file processing you may want to generate icons for available image thumbnails. Specifically, many JPEG images contain EXIF thumbnails, you could considerably speedup the reads by using decoded thumbnails to feed into func Icon. External packages to read thumbnails: 1 and 2. A note of caution: in rare cases there could be issues with thumbnails not matching image content. EXIF standard specification: 1 and 2.

To search in very large image collections (billions or more), use preliminary hash-table-based filtering with package imagehash.