b2KIT

Image Hash Calculator

Calculate perceptual hash, MD5, SHA-256, and other hashes of image files.

Tested tool guide Tested browser tools Checked August 16, 2026

What Image Hash Calculator does and how it behaves

Choose an image file to obtain two different kinds of identifiers: byte-for-byte digests such as MD5 and SHA-256, and a perceptual hash intended for comparing visual content. The file is processed entirely in the browser and is not uploaded. The important distinction is that exact digests describe the complete encoded file, not merely its visible pixels. Two images that look identical can therefore have different digests because their formats, compression settings, color profiles, metadata, or container details differ.

How the result is produced

1

Exact file digests

For MD5, SHA-256, and any other exact digest displayed, the input is the image's complete byte sequence. The same bytes processed with the same algorithm produce the same value. Headers, metadata, embedded profiles, and compressed image data all contribute. SHA-256 is the appropriate displayed choice when checking integrity against a trusted digest.

2

Perceptual fingerprint

The perceptual hash serves a different comparison task. It summarizes image appearance so that resized, recompressed, or modestly altered versions may remain more closely related than their exact digests suggest. The hash is not a similarity percentage or an integrity guarantee. Meaningful comparison requires results produced by the same perceptual-hash method and an appropriate distance rule.

Good uses

  • Compare the SHA-256 digest of a downloaded image with a value supplied through a trusted channel, allowing byte-level corruption or replacement to be detected.
  • Group byte-for-byte duplicate photographs before archiving or organizing a collection, while reviewing filenames, locations, and backups before removing any copy.
  • Screen an image collection for resized, recompressed, or lightly edited versions of a reference picture by comparing perceptual hashes, then visually inspect likely matches.

Limits and checks

  • Do not compare an MD5 value with a SHA-256 value. Equality is meaningful only between digests calculated with the same named algorithm, and a longer-looking value is not simply a more detailed version of a shorter one.
  • MD5 is vulnerable to deliberately constructed collisions. It can still label ordinary duplicate files, but it should not be treated as proof that adversarial content is authentic or unchanged.
  • A perceptual hash can match unrelated pictures or differ after an edit a person considers minor. It supplies a resemblance signal, not proof of identity, authorship, provenance, ownership, or duplication.

Common questions

Which result should I use to check whether an image was modified?

Use SHA-256 when you possess a trusted SHA-256 value for the exact original file and need a byte-level integrity check. Use the perceptual hash when re-encoding, resizing, or similar presentation changes are expected and you want to find visually related candidates. No perceptual match can certify that an image is authentic or unaltered.

Why did resaving an unchanged-looking image produce new hashes?

Saving again can rewrite compression data, metadata, color-profile information, field ordering, or container structures even when the rendered picture appears unchanged. MD5 and SHA-256 cover all those bytes, so different values are expected. The perceptual hash may remain related, but that depends on the resulting visual content and the perceptual method used.

References and verification

The behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.

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