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Image Hash Calculator

This tool helps you create visual fingerprints for deduplication, QA checks, or asset library audits without uploading your files.

Hash types and usage

Unlike cryptographic hashes (like SHA-256) that change with a single byte, perceptual hashes tolerate minor visual changes. You can enable aHash (brightness), dHash (gradients), pHash (low-frequency structure), and wHash (wavelet structure).

Using a mix of these algorithms gives a broader fingerprint. For quick scans, aHash and dHash are fast and reliable. For stronger comparisons involving compressed or resized variants, pHash and wHash are more robust.

8×8 vs 16×16 hash size

The 8×8 hash creates a 64-bit fingerprint that is quick to calculate and easy to compare, making it the practical default for most checks.

The 16×16 option produces a 256-bit fingerprint. It takes slightly longer to compute but provides a much more sensitive hash for comparing detailed structure in larger workflows.

Batch calculation and export

After you add your images, the tool decodes and hashes them entirely client-side. You can copy individual hashes or all hashes for a single image directly from its card.

When you have processed an entire batch, download the results as a CSV. This export includes the filenames, MIME types, dimensions, and all selected hashes, giving you a clean dataset for your audit or comparison scripts.

Frequently Asked Questions

It generates perceptual image hashes for JPEG, PNG, and WebP files directly in your browser. You can calculate aHash, dHash, pHash, and wHash values, copy them from each image card, and export the results as a CSV file.

JPEG, PNG, and WebP images are supported. These are the most common image formats used in everyday web workflows.

No.

An image hash is a compact fingerprint generated from an image. Perceptual image hashes are designed to describe visual structure, so similar images may produce similar hashes even if the files are not byte-for-byte identical.

aHash uses average brightness, dHash uses differences between neighboring pixels, pHash uses frequency information, and wHash uses wavelet-based image structure. Each method captures visual similarity in a slightly different way.

No. MD5, SHA-1, and SHA-256 are cryptographic file hashes that change completely if even one byte changes. Perceptual hashes are image-focused and are meant to be more tolerant of visual changes such as resizing or compression.

This tool generates the hashes you need for duplicate or near-duplicate workflows. The current tool focuses on calculation and export; image comparison can be handled separately using the generated hashes.

Use 8×8 for quick 64-bit hashes and simpler workflows. Use 16×16 for 256-bit hashes when you want a more detailed fingerprint and do not mind slower calculation.

Yes. Each image card shows the enabled hash types and includes a Copy button for each generated hash.

Yes. Each card includes a Copy all button that copies the filename, image details, and all enabled hashes for that image.

Yes. After hashing images, you can download a CSV file containing filename, MIME type, file size, dimensions, and the enabled hash values.

Yes. Once the page has loaded, the tool can work offline because image decoding and hash calculation happen locally in the browser.

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