Cold Case Detectives Are Using AI to Colorize Old Crime Photos

My neighbor Linda has a cork board. Not the "grocery list and dentist appointment" kind of cork board. The wall-spanning, red-string-connecting, photocopied-newspaper-clipping kind. Linda is, in her own words, a "hobbyist investigator." The rest of us call her a true crime podcast addict who has taken things approximately seventeen steps too far. Last spring, she knocked on my door holding a printed grayscale photo of a man who went missing from our county in 1987 and asked, with complete sincerity, if I could "run it through the color machine." I had no idea what she meant. But forty minutes later, we both did.

The Problem with Decades-Old Photos

Here is something nobody tells you about historical photos: the human brain is genuinely bad at recognizing faces in grayscale. This sounds absurd, but it is a documented phenomenon. Color carries an enormous amount of identity information. Hair that reads as "dark" in a 1960s school portrait could be auburn, chocolate brown, or jet black. A "light" jacket in a 1974 surveillance frame could be cream, pale blue, khaki, or mint green. Witnesses describe what they remember in color. Grayscale robs you of the matching layer.

This is why documentary filmmakers spend small fortunes colorizing archival footage. It is why historians argue passionately about the exact shade of Abraham Lincoln's eyes (hazel, for the record, though the debate continues). And it is why amateur sleuths like Linda, and increasingly professional investigators, genealogists, archivists, and journalists, are turning to AI colorization to make old images actually usable.

What AI Colorization Actually Does

The technology behind modern AI colorization is genuinely impressive, and not in the hand-wavy "machine learning magic" way that tech articles love to deploy. The neural networks behind tools like COMBb2's Colorize tool have been trained on millions of paired images, learning the statistical relationships between grayscale tonal values and realistic color outputs. The model essentially asks: "Given the texture, context, and luminosity of this region, what color is it most likely to be?"

Skin tones, vegetation, sky, wood grain, fabric weaves, brick, concrete: the AI has seen enough of all of these to make highly educated guesses. It is not inventing color at random. It is doing something closer to what a conservator does when restoring a faded painting, inferring from context and material knowledge what was probably there originally.

What it cannot do is read minds. If someone in a 1952 photo is wearing a red coat and a green hat, the AI will almost certainly get the coat right and might guess the hat wrong. AI colorization is probabilistic, not psychic. (We wrote an honest breakdown of exactly this in our accuracy and limitations guide if you want the full picture before you start.)

Where This Actually Matters Beyond True Crime

Linda's cork board is entertaining, but the real-world applications of AI colorization are broader and more serious than one might expect.

Family Genealogy Research

Ancestry research has exploded in the last decade, driven partly by DNA kit companies and partly by a collective pandemic-era urge to find out where we came from. The problem is that most family photos predating the 1970s are in black and white, and people look profoundly different in grayscale than they do in the living world. Colorizing a great-grandmother's portrait does not just make a prettier image. It makes a more emotionally resonant one. Families report feeling a genuine connection shift when they see an ancestor rendered in the colors they actually lived in.

Historical Journalism and Documentary Work

Journalists working on retrospective pieces about events from the mid-20th century or earlier routinely need to make archival images accessible to modern audiences. A grayscale photograph of a 1943 factory floor is interesting. That same photograph with accurate color applied to the machinery, the workers' clothing, and the light streaming through dusty windows is arresting. It closes the psychological distance between then and now.

Museum and Archive Digitization

Institutions that are digitizing physical collections often want to offer colorized versions alongside the original grayscale for educational materials, social media, and outreach. The constraint is usually budget. Hiring a professional colorist to hand-paint hundreds of archival photographs is expensive. AI handles the bulk work. Human review handles the nuance.

How to Get the Best Results

Linda's first attempt with the 1987 photo produced a result that was, charitably, "impressionistic." The original scan was low-resolution, slightly blurry, and had some water damage in the corner. We learned a few things the hard way, so you do not have to.

• Start with the best possible scan. AI colorization works with whatever tonal information exists in the grayscale image. A soft, underexposed scan gives the model less to work with. If your source image is blurry, consider running it through sharpening first to recover edge detail before colorizing.
• Resize for quality, not convenience. Tiny images produce muddy colorization results. If your historical photo is small, upscale it before processing.
• Manage your expectations for clothing. The AI is confident about skin, sky, and natural materials. Fashion colors are genuinely unpredictable, especially anything that was trendy in a specific decade. A 1968 minidress could be any of seventeen colors and the model will pick one.
• Treat the output as a starting point. The colorized version is a hypothesis, not a verdict. Use it to understand the image better, not as definitive historical record.

The Privacy Angle Nobody Mentions

Here is something worth noting when you are working with photos of real people, even historical ones. If you are uploading sensitive archival images to a web-based tool, you want to be certain those images are not being stored, processed remotely, or used for training data. With COMBb2, the colorization happens entirely in your browser. The photo never leaves your device. For genealogists handling private family collections, historians working with sensitive archival material, or yes, neighbors with cork boards full of cold case documents, that matters more than most tool comparison articles will admit.

Back to Linda

We ran the 1987 photo through the colorizer after first sharpening the scan and cleaning up the contrast. The result was not a miracle. But it was genuinely useful. The man's hair, which had read as an ambiguous dark tone in grayscale, resolved to a warm brown with reddish undertones. His jacket, previously just "light," became a plausible pale blue. Linda immediately said "that changes things" with the gravity of someone who absolutely watches too many true crime shows.

Whether or not it actually changes anything for a 37-year-old missing persons case is a question beyond my expertise. But the image was more legible, more human, and more recognizable than it had been. That is the real value of colorization. Not magic. Not forensic proof. Just a little more of the truth, visible.

Conclusion

AI colorization is one of those tools that sounds like a novelty until you actually need it, and then it becomes indispensable. Whether you are a genealogist trying to connect with an ancestor, a journalist bringing a historical moment to life, or simply someone who found a shoebox of grayscale prints in an attic, adding color to old photos changes how you see them. The Colorize tool handles the technical heavy lifting in your browser without touching a server, which means your family's history stays exactly where it belongs. Give it a try on something that matters to you. Just maybe do not build a cork board about it afterward.