Description: Histogram segmentation is an image segmentation method that uses the histogram of pixel intensities to separate different regions within an image. This approach is based on the premise that images can be analyzed and divided into homogeneous areas, where each area presents similar characteristics in terms of brightness or color. The histogram, which is a graphical representation of the distribution of pixel intensities, allows for the identification of the most common intensity levels and, from these, establishes thresholds that facilitate the separation of different regions. This method is particularly useful in images with sharp contrasts, where intensity differences are evident. Histogram segmentation can be implemented either automatically or manually, depending on the complexity of the image and the analysis requirements. Furthermore, it is a fundamental process in various computer vision applications, as it allows for the extraction of relevant features for tasks such as object recognition, edge detection, and image classification. Its simplicity and effectiveness make it a widely used technique in image processing, serving as a crucial first step in many visual analysis systems.
