<p>Here is a quote from the abstract of a paper which I think would answer your question:</p>
<blockquote>
<p>In images with uniform contrast distribution of background and
foreground like document images, global thresholding is more
appropriate. In degraded document images, where considerable
background noise or variation in contrast and illumination exists,
there exists many pixels that cannot be easily classified as
foreground or background. In such cases, binarization with local
thresholding is more appropriate.</p>
</blockquote>
<p>Reference: <a href="http://arxiv.org/pdf/1201.5227v1.pdf" rel="nofollow noreferrer">click me</a></p>
<p>If something is unclear please ask for clarification :)</p>
Segmentation using a thershold
<p>I need to segment an object from background. As the starting point I assume there is a single object in the image and my task is to separate it from the background and create a binary image ( 0 -for background and 1 - for object). I read some stack overflow questions and research papers about segmentation using threshold. I have found two ways, global threshold and local/adaptive threshold. We can apply them under various conditions i.e. global threshold may be suitable for one case but may not be suitable for other case. My question is given an image how we can automatically find the most appropriate method. Is it always suitable to use local threshold approach instead global as a precaution?</p>