{"url":"/dataset/thermal-focus-image-database","name":"Thermal focus image database","full_name":null,"description_markdown":"The database was acquired using a thermographic camera TESTO 880-3. This camera is equipped with an uncooled detector and has a spectral sensitivity range from 8 to 14 μm. It has a removable German optic lens. It provides the following main features:\r\n\r\nImage resolution: 160 × 120 pixels.\r\nOptical field/min. focus distance: 32° × 24°/0.1 m.\r\nThermal sensitivity (NETD) <0.1 °C at 30 °C.\r\nGeometric resolution: 3.5 mrad.\r\nDetector type: FPA 160 × 120 pixels, temperature-stabilized.\r\nThe database consists of several image sets. In each set, the camera acquires one image of the scene at each lens position. In our case we have manually moved the lens in 1 mm steps which provides a total of 96 positions. Thus, each set consists of 96 different images of the one scene. For this purpose, we have attached a millimeter tape to the objective, and used a stable tripod in order to acquire the same scene for each scene position. to add a brief description of the dataset (Markdown and LaTeX enabled).\r\n\r\nProvide:\r\n\r\n* a high-level explanation of the dataset characteristics\r\n* explain motivations and summary of its content\r\n* potential use cases of the dataset\r\nWe acquire different kinds of images according to their information content and depth of focus. It should be easier to focus an image with large amount of detail, because blurring in such an image will generally be more evident. As in visible images, it should be more difficult to completely focus an image with several objects, when each object is located at a different focal distance. We analyzed only static scenes, because of the need for comparability (same position and temperature).\r\nWe have constructed 10 different databases, as follows.\r\n\r\nTelematic equipment (TE): this consists of four sets of images of the same scene (an item of telematic equipment). Set one (TE1) is acquired at one meter distance from the scene to the camera, set two (TE2) is acquired at two meters, set three (TE3) at three meters and set four (TE4) at 4 m. Obviously, when moving the camera away from the scene, more objects appear in the image. On the other hand, these four databases contain a scene that can be considered to be contained in a flat plane. Thus, it is acquiring mainly a two dimensional object with a single point of focus.\r\nElectronic circuit (EC): this consists of a single set of images of the same scene (an electronic circuit with components at different temperatures and distances from the camera). It is important to emphasize that, in this case, we are acquiring a very near object, in which there is a range of depth. Thus, it is not possible to focus the whole image simultaneously.\r\nLaptop transformer (LT): this consists of a single set of images of the same scene (the transformer of a laptop computer).\r\nCorridor and fluorescents (CF): this consists of a single set of images of a single scene (a corridor at the university, illuminated by several ceiling fluorescents).\r\nHeater (H): this consists of a single set of images of a heater. This scene contains a large amount of detail because the metallic parts are warmer than the spaces between.\r\nFace (F): this consists of a single set of images of a human face. This sequence contains a scene that is not fully static because of involuntary physical movement (eyes, breathing, etc.).\r\nHand (Ha): this consists of a single set of images of a hand. The hand rests on a black surface.\r\nThe database consists of 10 × 96 = 960 images.","description_withheld":null,"homepage":"http://splab.cz/en/download/databaze/thermal-focus-image-database","introduced_date":"2011-11-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/on-the-focusing-of-thermal-images","title":"On the focusing of thermal images","first_author":"Marcos Faundez-Zanuy","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Thermal focus image database"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}