Image Segmentation – A State-Of-Art Survey for Prediction

Image segmentation is a technique that partitioned the input image into prerequisite semantic unique regions. Segmentation should stop as object of interest in an application is isolated. The ultimate goal is to make the image more simplified one and that to get more meaningful to analyze. Number of segmentation techniques are available but none of them satisfy the global properties and thus remain challenge for researcher. Many computer applications like object recognition, automatic pictorial pattern recognition, automatic traffic control are based on this analysis. As per need of an application segmentation techniques can be selected. This survey addressed various segmentation techniques, discussed fundamental methodologies, and issues related with specific techniques. It discussed its limitations and probable solution to recover it. It also includes discussion on segmentation technique based on graph partitioning which would be helpful to add intelligence for prediction. Concept of ontology is introduced in short as technical bridge in between segmentation and image prediction.