prahování

Prahování, also known as thresholding, is a fundamental image segmentation technique used in computer vision and image processing. It is a simple yet effective method for separating an image into distinct regions based on pixel intensity values. The core principle of prahování is to establish a threshold value. Pixels with an intensity greater than this threshold are assigned one value (typically white or 1), while pixels with an intensity less than or equal to the threshold are assigned another value (typically black or 0). This process effectively converts a grayscale image into a binary image.

There are several variations of prahování. Global prahování uses a single threshold value for the entire image. This is suitable when the image has good contrast and a clear separation between foreground and background. However, in images with varying illumination conditions, global prahování can lead to suboptimal results. Adaptive prahování addresses this limitation by calculating different threshold values for different regions of the image. This is achieved by considering a small neighborhood around each pixel and calculating the threshold based on the local statistics of that neighborhood. Common adaptive methods include Otsu's method, which automatically determines an optimal global threshold by minimizing the intra-class variance, and local adaptive methods that compute thresholds based on local averages or weighted sums. Prahování is widely used in applications such as object detection, optical character recognition (OCR), and medical image analysis.