Abstract
Image segmentation is a process of partitioning an image into different regions that are homogeneous or “similar” in some image characteristics. These regions may roughly correspond to objects, parts of objects, or groups of objects in the scene represented by that image. It can also be viewed as the process of identifying edges that correspond to boundaries between objects, and regions that correspond to surfaces of objects in the image. Segmentation of an image typically precedes semantic analysis of the image. Its purposes are [61]:
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Data reduction the number of important features, i.e., regions and edges, is much smaller than the number of pixels
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Feature extraction the features extracted by segmentation are usually “building blocks” from which object recognition begins. These features are subsequently analyzed based on their characteristics
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© 1994 Springer Science+Business Media New York
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Bhanu, B., Lee, S. (1994). Introduction. In: Genetic Learning for Adaptive Image Segmentation. The Springer International Series in Engineering and Computer Science, vol 287. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2774-9_1
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DOI: https://doi.org/10.1007/978-1-4615-2774-9_1
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