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Improved method for finding subimages with maximal property

[Category : - SOFTWARES]
[Viewed 1481 times]

Image analysis and pattern recognition continue to be developing and fruitful disciplines. Evaluating images to locate a subimage with maximal property is a frequent operation. For example, an object or subimage of a certain color is searched for within an image of many objects, as seen in the images above.

This operation is currently very costly in terms of computing time and, therefore, computing power, due to the underlying algorithm used to produce its result. US Patent 62207354: “Improved method for finding subimages with maximal property” has been proven to run approximately six (6) times faster than today’s method. In other words, this patent’s method can produce six results in the same time that today’s method would produce just one.

There is one accuracy disadvantage to this patent’s method; however, this disadvantage is negligible within the context of image evaluation. The accuracy discrepancy is as follows: on average, this patent’s method will locate a subimage with maximal property whose value is 99.9% that of the images truly maximal subimage. This is negligible within the context of image evaluation because any subimage with close to maximal property will be sufficient. For example, in the images above, imagine that both today’s method and this patent’s method are searching for a blue subimage. Today’s method would identify a blue rectangle as in the above right image, while this patent’s method would identify a rectangle about 99.9% as large in comparison. In many cases, the output rectangles are equivalent. In the rare case that they are not, there are two rectangles with very similar properties, such that if one were detecting, say, apples in an image of many fruits, today’s method and this patent’s method may identify different apples, but they will both still identify apples.

Imagine the applications of this patent’s method: performing object and color detection on any image, except six times faster. This improvement could be used among virtually every technological field, such as artificial intelligence, face detection, pedestrian detection, and image processing.

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