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Download e-book for kindle: Natural Object Recognition by Thomas M. Strat

By Thomas M. Strat

ISBN-10: 1461229324

ISBN-13: 9781461229322

ISBN-10: 1461277256

ISBN-13: 9781461277255

Natural item Recognition offers a unconditionally new method of the automation of scene realizing. instead of trying to build hugely really expert algorithms for spotting actual items, as is common in glossy laptop imaginative and prescient examine, the appliance and next evaluate of huge numbers of fairly simple photo processing workouts is used to acknowledge common gains corresponding to bushes, timber, and rocks. using contextual info is the main to simplifying the matter to the level that good understood algorithms provide trustworthy ends up in ground-level, outdoors scenes.

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Extra info for Natural Object Recognition

Sample text

As can be seen, the layered partition need not assign every pixel to a region, nor does it need to assign each pixel to only one region. The layered partition has these advantages over the ordinary partition: • Ambiguous pixels can be represented explicitly. For example, some pixels in the tree crown may be indistinguishable as sky or foliage. The layered partition allows those pixels to occur in regions for both sky and foliage. 32 2. 6. A representative image of sparsely scattered trees. 7. An ordinary partition vs.

NATURAL OBJECT RECOGNITION Of course, context is not necessary for everything. Many artifacts and some natural objects, such as a bird or a pine cone, can be instantly recognized even when all contextual clues have been removed. It is also possible to recognize some scenes in which contextual constraints have been violated. An image of an office scene with a telephone on the floor is unusual but not impossible to recognize. An image turned sideways is instantly recognized as such, despite the fact that relevant contextual knowledge is violated.

A rock or a river). 1). Indeed, most natural objects fail this line drawing test, which requires identification based solely on observed shape. Similarly, when resolution is too coarse to discern shape, recognition is often 20 2. 1. Recognition by shape: The telephone is recognizable from edges extracted from an image, but the river is not. 3. Limitations of current machine-vision technology 21 possible on the basis of size and context. 5D sketch, as a significant intermediate representation in image understanding.

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Natural Object Recognition by Thomas M. Strat


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