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Statistical Models of Shape
Rhodri Davies
Carole Twining
Chris Taylor
其他書名
Optimisation and Evaluation
出版
Springer Science & Business Media
, 2008-12-15
主題
Computers / Software Development & Engineering / Computer Graphics
Computers / Artificial Intelligence / Computer Vision & Pattern Recognition
Computers / Optical Data Processing
Computers / Software Development & Engineering / General
ISBN
184800138X
9781848001381
URL
http://books.google.com.hk/books?id=Lk1dF-GXvwEC&hl=&source=gbs_api
EBook
SAMPLE
註釋
The goal of image interpretation is to convert raw image data into me- ingful information. Images are often interpreted manually. In medicine, for example, a radiologist looks at a medical image, interprets it, and tra- lates the data into a clinically useful form. Manual image interpretation is, however, a time-consuming, error-prone, and subjective process that often requires specialist knowledge. Automated methods that promise fast and - jective image interpretation have therefore stirred up much interest and have become a signi?cant area of research activity. Early work on automated interpretation used low-level operations such as edge detection and region growing to label objects in images. These can p- ducereasonableresultsonsimpleimages,butthepresenceofnoise,occlusion, andstructuralcomplexity oftenleadstoerroneouslabelling. Furthermore,- belling an object is often only the ?rst step of the interpretation process. In order to perform higher-level analysis, a priori information must be incor- rated into the interpretation process. A convenient way of achieving this is to use a ?exible model to encode information such as the expected size, shape, appearance, and position of objects in an image. The use of ?exible models was popularized by the active contour model, or ‘snake’ [98]. A snake deforms so as to match image evidence (e.g., edges) whilst ensuring that it satis?es structural constraints. However, a snake lacks speci?city as it has little knowledge of the domain, limiting its value in image interpretation.