3 - Images Databases 1. Raw Images The content of an image...

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Images Databases 1. Raw Images The content of an image consists of all object in that image that are deemed to be interest from the point of view of an application Such object in an image have a variety of associated properties such as Shape descriptor : that describes the shape/location of the region within which the object is located inside a given image Property descriptor : that describes the properties of the individual pixel (or group of pixel) Ex. Shape descriptor: XLB= 10,XUB=60,YLB=10m YUB=100 property descriptor: red=5, green=1, blue=3 Each image I has an associated pair of positive integer (m,n) called the gride resolution of the image this divides the image into (m,n) cells of equal size called the image grid. Each cell in a given gridded (m,n) image I consists of a collection of pixels A cell property is a triple (name, values, method) where: Name is a string denoting the property’s name Value: is a set of values that the property may assume Method: is an algorithm that tells us how to compute the property value
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Ex for an black and white image (bwcolor, {b,w}, bwalgo) In general, software engineers who are constructing an image database application must first decide which cell properties are of interest and then create methods associated with determining these properties An object shape is any set P of points such that P 1 ,…P n P For any point Pi where 1 ≤ I ≤ n the pint P i+1 is a neighbor of P i If P i+1 =(X i ,Y i ) and P i+1 = (Xi+1, Yi+1) satisfies one of the following conditions P i (X i+1, Y i+1 ) = (X i +1 , Y i ) (X i+1 , Y i+1 ) = (X i -1, Y i ) (X i+1 , Y i+1 ) = (Xi, Yi+1) (X i+1 , Y i+1 ) = (Xi, Yi-1) (X i+1 , Y i+1 ) = (Xi+1, Yi+1) (X i+1 , Y i+1 ) = (Xi+1, Yi-1) (X i+1 , Y i+1 ) = (Xi-1, Yi+1) (X i+1 , Y i+1 ) = (Xi-1, Yi-1) We will only consider objects that have a rectangular shape in this course Rectangle is an object shape P such that there exist integers XLB, XUB, YLB, YUB An Image database (IDB) consists of a triple (GI, Prop, Rec) GI is a set of gridded images of the form (m,n) Prop is a set of cell properties Rec is a mapping that associates with each image (a set of rectangles denoting objects)
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Note that when representing image data of the form described above two major factors must be taken into account First, images are often very large objects consisting of (P1, P2) pixel array Explicitly storing properties on a pixel by pixel basis is usually infeasible This has to led to family of images compression algorithm that attempt to compress the image into one fewer pixels Second, given an image I (compressed, or raw) there is a critical need to determine what feature appear in the image This is typically done by breaking up the image into a set of homogeneous rectangular regions (with the respect to some properties) Each of which called segment
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This note was uploaded on 04/12/2011 for the course IS 505 taught by Professor Drmohamed during the Spring '11 term at Cairo University.

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3 - Images Databases 1. Raw Images The content of an image...

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