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- W1487687742 abstract "Shape matching plays important roles in many fields such as object recognition and image retrieval. A recently proposed novel matching algorithm called shape utilizes relationship of points on boundary of to all other points on boundary as a descriptor. The magnitude of alignment between two shapes so described is distance between contexts of comparison shapes. The context was shown to be an information rich descriptor that is invariant to translation, scale, and rotation. To determine distance between two shapes that have been abstracted into contexts problem was modeled as a bi-partite matching problem know as the assignment problem. While performing well, nature of assignment problem limits effectiveness of matching. Using graph theory, a proof is provided that shows that certain geometrically different shapes are considered identical by context algorithm. By limiting domain of shapes to those of continuous boundaries and using fact that an order does exit for points on boundary, a more effective matching algorithm, entitled the least cost diagonal is presented and explored. Finally, least cost method is applied in a real world application of automobile identification and compared to same application but using assignment problem model for matching." @default.
- W1487687742 created "2016-06-24" @default.
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- W1487687742 date "2006-01-01" @default.
- W1487687742 modified "2023-09-26" @default.
- W1487687742 title "Shape matching with ordered boundary point shape contexts using a least cost diagonal method" @default.
- W1487687742 hasPublicationYear "2006" @default.
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