Older photos only exist in black and white. The non-existent colors of such photographs thus represent fragments of lost history. The master's thesis deals with the coloring of black-and-white photographs. We colorized the photos with the wisdom of the crowds, which is a new approach. We created a measuring instrument (web application) and conducted a survey on the participants. In calculating the distances between colors, we used mathematical models that are most relevant to human perception of colors. We compared the results of the crowd with the results of the algorithm, looked for categorical differences in participants, and looked at how the reliability of the result of the crowds varies with the number of participants. We showed that with more participants, the error converges to some value. Men and women pick color about equally well, but men's choices are more diffuse. We compared the results of the crowd with the results of an algorithm based on deep neural networks. Compared to the algorithm, people were solving better tasks where contextual knowledge is needed. The new method of coloring black-and-white photographs with the wisdom of the crowds looks promising, but more research is needed.
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