Segmentation techniques in image processing using matlab

Segmentation techniques are used to isolate the desired object from the scene so that measurements can be made on it subsequently. It includes edge detection, noise, Histogram modelling testing. Color-based Segmentation such as K-means clustering.

It provides an explicit means of recording design decisions and the context in which they were made.

Segmentation techniques in image processing using matlab
Transform methods such as watershed segmentation. And manipulate regions of interest ROIs. Selective focus photography of blue bird.
See other functions in the next section. The objective of segmentation technique in this paper is to partition a given image into regions or components for extracting objects from an image.

Most artist and painters used a modern technique in painting like indirect painting or glazes.

Segmentation techniques in image processing using matlab — photo 1
Segmentation subdivides an image into its constituent regions or objects. Cartoon vector illustration of elderly couple on motorbike. Segmentation or contouring could be also obtained using morphological operations. The background region refers to the region which is outside of the interested areas. One method for such separation is known as watershed segmentation.