Sniðmátsleit

Sniðmátsleit, often translated as "pattern matching" or "template matching" in English, is a technique used in computer vision and image processing to find occurrences of a known template image within a larger source image. The core idea is to slide the template image across the source image, performing a comparison at each possible position. The comparison typically involves calculating a similarity score, which indicates how well the template matches the underlying pixels of the source image.

Various metrics can be used to quantify this similarity. Common methods include Sum of Squared Differences (SSD), which measures the sum of the squared differences between pixel intensities, and Normalized Cross-Correlation (NCC), which is less sensitive to variations in illumination and contrast. A higher score generally indicates a better match. After calculating the similarity score for all positions, a threshold is applied to identify regions where the template is considered to be present.

Sniðmátsleit is a fundamental algorithm with applications in object detection, image registration, and feature recognition. It is relatively straightforward to implement but can be computationally intensive, especially for large images or complex templates. Variations and optimizations exist to improve its efficiency and robustness, such as using integral images or employing hierarchical search strategies. Despite its simplicity, sniðmátsleit remains a valuable tool in the image analysis toolkit.