Thresholding in image processing is used to convert a gray scale image to binary format, where only two values are possible for the pixel, zero ore one. Thresholding can be viewed as the simplest method of image segmentation. Thresholding is common step in an image analysis, where we need to differentiate the pixel area by two different brightness area, for example between object and the background.

Thresholding is the simplest method of image segmentation. From a gray scale image, thresholding can be used to create binary image (Shapiro, et al 2001:83).

During the thresholding process, individual pixels in an image are marked as “object” pixels if their value is greater than some threshold value (assuming an object to be brighter than the background) and as “background” pixels otherwise. This convention is known as threshold above. Variants include threshold below, which is opposite of threshold above; threshold inside, where a pixel is labeled "object" if its value is between two thresholds; and threshold outside, which is the opposite of threshold inside (Shapiro, et al 2001:83).
The most important key in the thresholding process is the threshold point. Manually, the threshold pint can be visually judged by trial and error, adjusting the value is you don't get the desired background-object separation.

For Automatic thresholding, many methods have been implemented in many research. You can simply use the mean or median value, or you can analyze the histogram and find a valley for the threshold value.

1 comment:

sarah lee said...

Try not to become a man of success, but rather try to become a man of value. See the link below for more info.