Natural scene images are captured at a larger distances to include details in scenery. It is much difficult to identify categories because of uncertain shapes & forms present inside these images. Such ambiguous form of nature, which lacks sharp boundaries, makes discrimination among the classes a complex task. This paper attempts to measure this ambiguity. A natural scene image also can belong to multiple categories at a time which makes a task of classification much more difficult and often leads to classification errors. Binary classification fails to capture this ambiguity while doing multi label classification of the image. This problem can be handled by using fuzzy membership function with assumption that class categories in a natural image are non-mutually exclusive. This work provides a ranking based class membership instead of binary classification.

Fuzzy Membership Function, Multi-Label Classification, Ranking, Supervised Learning

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