Error Level Analysis (ELA) Detector

This module provides a function to perform Error Level Analysis (ELA) on images to detect potential manipulations or edits.

Function: `run_ela`

def run_ela(image: Image.Image, quality: int = 90, threshold: int = 15) -> bool:

Description

Error Level Analysis (ELA) works by recompressing an image at a specified JPEG quality level and comparing it to the original image. Differences between the two images reveal areas with inconsistent compression artifacts — often indicating image manipulation.

The function computes the maximum pixel difference across all color channels and uses a threshold to determine if the image is likely edited.

Parameters

Parameter	Type	Default	Description
`image`	`PIL.Image`	N/A	Input image in RGB mode to analyze.
`quality`	`int`	90	JPEG compression quality used for recompression during analysis (lower = more compression).
`threshold`	`int`	15	Pixel difference threshold to flag the image as edited.

Returns

bool

True if the image is likely edited (max pixel difference > threshold).
False if the image appears unedited.

Usage Example

from PIL import Image
from detectors.ela import run_ela

# Open and convert image to RGB
img = Image.open("example.jpg").convert("RGB")

# Run ELA detection
is_edited = run_ela(img, quality=90, threshold=15)

print("Image edited:", is_edited)

Notes

The input image must be in RGB mode for accurate analysis.
ELA is a heuristic technique; combining it with other detection methods increases reliability.
Visualizing the enhanced difference image can help identify edited regions (not returned by this function but possible to add).

Installation

Make sure you have Pillow installed:

pip install pillow

Running Locally

Just put the function in a notebook or script file and run it with your image. It works well for basic images.

Developer

Pujan Neupane