. . . "Vysok\u00E9 u\u010Den\u00ED technick\u00E9 v Brn\u011B" . . "Using Threshold Techniques for Object Detection in Infrared Images"@en . . "G43" . . . "2014-01-01+01:00"^^ . . "RIV/60162694:G43__/14:00523130" . "[2FA259D0D8C3]" . "RIV/60162694:G43__/14:00523130!RIV15-MO0-G43_____" . "Using Threshold Techniques for Object Detection in Infrared Images" . "52500" . "Brno" . . "http://vavtest.unob.cz/registr" . "Brno" . . . "Using Threshold Techniques for Object Detection in Infrared Images" . "Using Threshold Techniques for Object Detection in Infrared Images"@en . "2"^^ . "I, S" . . "The techniques for image format conversion from grayscale to binary could be grouped into two categories: global group and local group. In this paper, we focus on the binarization of a grayscale image using both thresholding techniques. Local binarization methods try to compute thresholds individually for each pixel, using information from the local neighborhood of the pixel. These methods are often slow since the computation of image features from the local neighborhood is to be done for each image pixel. This paper focuses on employing a fast approach to compute local thresholds using the technique of integral sum image. Using this approach we are able to achieve binarization speed close to the global binarization methods. What more, the Otsu method was used representing the other techniques in the global category. Global techniques are very fast and they give good results for typical images." . "Pol\u00E1\u0161ek, Martin" . "2"^^ . "8"^^ . . "Threshold techniques; Matlab; Object detection"@en . "The techniques for image format conversion from grayscale to binary could be grouped into two categories: global group and local group. In this paper, we focus on the binarization of a grayscale image using both thresholding techniques. Local binarization methods try to compute thresholds individually for each pixel, using information from the local neighborhood of the pixel. These methods are often slow since the computation of image features from the local neighborhood is to be done for each image pixel. This paper focuses on employing a fast approach to compute local thresholds using the technique of integral sum image. Using this approach we are able to achieve binarization speed close to the global binarization methods. What more, the Otsu method was used representing the other techniques in the global category. Global techniques are very fast and they give good results for typical images."@en . "Pham, Quy Ich" . . . . . "978-80-214-4817-9" . "Proceedings of the 16th International Conference on Mechatronics \u2013 Mechatronika 2014" .