The study of new types of dominance mechanisms is a key point in current evolutionary multiobjective optimization community and ε dominance is a representative among them. However, their ability in diversity maintaining is sensitive to different shapes of Pareto fronts. This paper proposes an improved ε dominance mechanism by Isomap, which employs Isomap to embed the original population to low dimensional manifold space. The intrinsic geometric structure of them is discovered and ε dominance is adopted to select data in the embedding space. Compared with traditional ε dominance, the mechanism does not lose valid solutions and can maintain a set of uniform-distributed solutions. In addition, the extreme solution-check operator is proposed to enhance the ability of holding extreme solutions of ε dominance. The detailed experimental comparison with NSGAII, SPEA2, NNIA and εMOEA shows that the two strategies in this study are beneficial to uniformity and spread maintenance, which are in the enhanced version of traditional ε dominance.