验证码识别 edge enhancement - 轮廓增强 region finding

Computer Science An Overview _J. Glenn Brookshear _11th Edition

The task of understanding general images is usually approached as a two-

step process: (1)

image processing,

which refers to identifying characteristics of

the image, and (2)

image analysis,

which refers to the process of understanding

what these characteristics mean. We have already observed this dichotomy in

the context of recognizing symbols by means of their geometric features. In that

situation, we found image processing represented by the process of identifying

the geometric features found in the image and image analysis represented by the

process of identifying the meaning of those features.

Image processing entails numerous topics. One is edge enhancement, which is

the process of applying mathematical techniques to clarify the boundaries between

regions in an image. In a sense, edge enhancement is an attempt to convert a

photograph into a line drawing. Another activity in image analysis is known as

region finding. This is the process of identifying those areas in an image that have

common properties such as brightness, color, or texture. Such a region probably

represents a section of the image that belongs to a single object. (It is the ability to

recognize regions that allows computers to add color to old-fashioned black and

white motion pictures.) Still another activity within the scope of image processing

is smoothing, which is the process of removing flaws in the image. Smoothing keeps

errors in the image from confusing the other image-processing steps, but too much

smoothing can cause the loss of important information as well.

Smoothing, edge enhancement, and region finding are all steps toward iden-

tifying the various components in an image. Image analysis is the process of

determining what these components represent and ultimately what the image

means. Here one faces such problems as recognizing partially obstructed objects

from different perspectives. One approach to image analysis is to start with an

assumption about what the image might be and then try to associate the compo-

nents in the image with the objects whose presence is conjectured. This appears

to be an approach applied by humans. For instance, we sometimes find it hard to

recognize an unexpected object in a setting in which our vision is blurred, but

once we have a clue to what the object might be, we can easily identify it.

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