In this paper, we have proposed an application of pattern recognition technique to recognize partially destroyed objects in debris. The study employs an appearance-based eigenspace technique for investigating the representation and recognition of partially destroyed objects, which is one of the severe limitations of this technique. Since the conventional parametric eigenspace technique cannot handle the occluded or even partially destroyed objects, we propose creation of a <i>mean-appearance </i>for representing and recognizing them. The word <i>mean-appearance </i>describes a mean image set, which allows some partially destroyed objects for producing an eigenspace. In the mean image set, averaging of a few destroyed images along with non-destroyed images make a mean appearance, which has less effect of partially destroyed images. In addition, we have proposed to apply eigenspace method to measure lost goods in debris when the conventional method will not be an alternative. The proposed approach is performed using various destroyed objects and experimental results show the effectiveness of the proposed method.