文件名称:0alaya-cheikh2004
介绍说明－－下载内容均来自于网络，请自行研究使用
Query by content, or content-based retri has recently been proposed as
an alternative to text-based retri for media such as images, video and audio.
Text-based retri is no longer appropriate for indexing such media, for several
reasons. Firstly, keyword annotation is labor intensive, and it is not even possible
when large sets of images are to be indexed. Secondly, these annotations are
drawn a predefined set of keywords which cannot cover all possible concepts
images may represent. Finally, keywords assignment is subjective to the person
making it. Therefore, content-based image retri (CBIR) systems propose to
index the media documents based on features extracted their content rather
than by textual annotations. For still images, these features can be color, shape,
texture, objects layout, edge direction, etc.-Query by content, or content-based retri has recently been proposed as
an alternative to text-based retri for media such as images, video and audio.
Text-based retri is no longer appropriate for indexing such media, for several
reasons. Firstly, keyword annotation is labor intensive, and it is not even possible
when large sets of images are to be indexed. Secondly, these annotations are
drawn a predefined set of keywords which cannot cover all possible concepts
images may represent. Finally, keywords assignment is subjective to the person
making it. Therefore, content-based image retri (CBIR) systems propose to
index the media documents based on features extracted their content rather
than by textual annotations. For still images, these features can be color, shape,
texture, objects layout, edge direction, etc.
an alternative to text-based retri for media such as images, video and audio.
Text-based retri is no longer appropriate for indexing such media, for several
reasons. Firstly, keyword annotation is labor intensive, and it is not even possible
when large sets of images are to be indexed. Secondly, these annotations are
drawn a predefined set of keywords which cannot cover all possible concepts
images may represent. Finally, keywords assignment is subjective to the person
making it. Therefore, content-based image retri (CBIR) systems propose to
index the media documents based on features extracted their content rather
than by textual annotations. For still images, these features can be color, shape,
texture, objects layout, edge direction, etc.-Query by content, or content-based retri has recently been proposed as
an alternative to text-based retri for media such as images, video and audio.
Text-based retri is no longer appropriate for indexing such media, for several
reasons. Firstly, keyword annotation is labor intensive, and it is not even possible
when large sets of images are to be indexed. Secondly, these annotations are
drawn a predefined set of keywords which cannot cover all possible concepts
images may represent. Finally, keywords assignment is subjective to the person
making it. Therefore, content-based image retri (CBIR) systems propose to
index the media documents based on features extracted their content rather
than by textual annotations. For still images, these features can be color, shape,
texture, objects layout, edge direction, etc.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
0alaya-cheikh2004.pdf