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Region-oriented segmentation in digital image processing (DIP) refers to techniques that partition an image into distinct regions based on predefined criteria, such as color, texture, or intensity. This approach focuses on identifying homogeneous areas within an image, allowing for more accurate object detection and recognition. Common methods include region growing, where pixels are added to a region based on similarity, and region splitting and merging, which divides an image into subregions and combines them based on certain characteristics. This segmentation is particularly useful in applications like medical imaging and satellite imagery, where precise region delineation is crucial.

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