An Intelligent Framework for Natural Object Identification in Images

Human superiority over computers in identifying natural objects like clouds, water, grass etc. comes from two capabilities: the capability to maintain a growing knowledge base pertaining to natural object attributes as experienced over a period of time, and the capability to tolerate variations inherently present in the attributes of natural objects. In this paper we aim to mimic both these capabilities for efficient machine identification of local objects in natural scene imagery through a combined application of Case Based Reasoning (CBR) and Fuzzy Logic (FL).Training data of natural objects is used offline to build a case base of various natural object attributes. The imprecision in the definition of natural objects is accommodated by employing fuzzy linguistic variables for object attribute description in the case base as well as in the similarity calculation and case retrieval procedures. When presented with a new image, the reasoning system applies fuzzy similarity concept to re...

• Type: Journal
• Year: 2010
• Where: IJACTAICIT
• Authors: Aasia Khanum
• Keywords: Case Base, IJACTAICIT 2010, Natural Objects, Various Natural Object