The wooden defects identification plays a vital role while making wooden materials. In order to find the defects in the wooden pieces is complex when these wooden raw materials grind in the mill. Our goal is obtain the wooden defects without producing any human efforts and cost. The wooden knots which affects the wooden creatures. Many companies take steps to avoid wooden materials with the knots and the defects. But it leads to more cost and need more number human resource. The feature can be

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... xtracted to obtain the results of defects. We propose NSGA II algorithm for aspect set extraction. The idea behind the NSGA II is that a ranking selection method is used to emphasize good points and a niche method is used to maintain stable subpopulations of good points. It differs from simple genetic algorithm only in the way the selection operator works.