Anti-Tricked, Here Are 5 Tools That Can Detect Edited Photos

Illustration of someone editing an image (photo: dock. Pixabay)

JAKARTA - The unclear source of image is often a problem on social media. These photos often cause a stir because there is no clarity between the original or fake.

To avoid this problem, photo recognition technology was finally developed. Now we can know whether photos that have gone viral on social media have been manipulated or not. Here are five edited photodetector tools, reported by Makeuseof.

This photo detection tool can show whether the photo we want to know has been edited or not. Image Edited can identify basic editing techniques and show raw EXIF data such as camera models, date, location, and various other information.

When using the Fake Image Detector, this tool will perform an Analysis of the Error Rate (ELA). Later, this tool will take into account image metadata to check whether uploaded images have been manipulated with an accuracy of 60 to 70 percent.

The edited photodetector tool that is quite popular is PhotoForensics. This tool uses various types of data such as ELA and metadata to find out the authenticity of a photo. When uploading photos on PhotoForensics, this tool will analyze and show a change in color. However, if the photo only shows white color, then the photo is detected as genuine.

This photo authenticity detection tool is not limited to ELAs like any other tool. With the generation ofhash digests, this tool creates a unique code for images based on data to detect image status. In addition, the extrastrict used can find hidden text in images such as URLs, dates, or others.

This downloadable program can analyze data. Later, the uploaded image results will be provided with important information such as dimensions and compression modes. JPEGsnoop also has a histogram feature that provides pixel value graphs in the image.

Those are the five edited image detectors. With these five tools, you don't need to worry anymore when you want to find out the authenticity of a photo.