A crack information detection device comprising: a crack information detection unit that detects crack information of a crack of a structure by an image analysis of a surface image of the structure, the crack information comprising a series of damage vectors; a labeling unit that assigns a label (C1-1, C1-2,...) for identifying crack information corresponding to a crack to each damage vector; a crack information editing unit that accepts manual editing of the crack information by a user; a registration unit that registers an editing result of the crack information, an operation history required for editing the crack information, and the label (C1-1, C1-2,...) in association with each other in a database; wherein the operation history required for editing the crack information includes (i) at least one of the number of operations required for deleting the pixels composing a damage vector or an operation time required for deleting the pixels composing a damage vector, or (ii) at least one of the number of operations required for adding the pixels composing a damage vector or an operation time required for adding the pixels composing a damage vector, or (iii) at least one of the number of operations required for adding the pixel connecting discontinuous damage vectors or an operation time required for adding the pixels connecting discontinuous damage vectors; a machine learning unit that updates a model for detecting the crack information by the crack information detection unit by specifying an editing history required to be learned based on the operation history of the crack information for each of the labels registered in the database and performing machine learning on a feature of a crack to be detected as a continuous crack or a discontinuous crack from the editing result corresponding to the specified editing history. a crack information detection unit that detects crack information of a crack of a structure by an image analysis of a surface image of the structure, the crack information comprising a series of damage vectors; a labeling unit that assigns a label (C1-1, C1-2,...) for identifying crack information corresponding to a crack to each damage vector; a crack information editing unit that accepts manual editing of the crack information by a user; a registration unit that registers an editing result of the crack information, an operation history required for editing the crack information, and the label (C1-1, C1-2,...) in association with each other in a database; wherein the operation history required for editing the crack information includes (i) at least one of the number of operations required for deleting the pixels composing a damage vector or an operation time required for deleting the pixels composing a damage vector, or (ii) at least one of the number of operations required for adding the pixels composing a damage vector or an operation time required for adding the pixels composing a damage vector, or (iii) at least one of the number of operations required for adding the pixel connecting discontinuous damage vectors or an operation time required for adding the pixels connecting discontinuous damage vectors; (i) at least one of the number of operations required for deleting the pixels composing a damage vector or an operation time required for deleting the pixels composing a damage vector, or (ii) at least one of the number of operations required for adding the pixels composing a damage vector or an operation time required for adding the pixels composing a damage vector, or (iii) at least one of the number of operations required for adding the pixel connecting discontinuous damage vectors or an operation time required for adding the pixels connecting discontinuous damage vectors; a machine learning unit that updates a model for detecting the crack information by the crack information detection unit by specifying an editing history required to be learned based on the operation history of the crack information for each of the labels registered in the database and performing machine learning on a feature of a crack to be detected as a continuous crack or a discontinuous crack from the editing result corresponding to the specified editing history.