关键词: 特征提取, 多重分形, 网格, 生长概率

Abstract: In order to solve the drawbacks of the multi-fractal dimension can not be a good reflection of the image intensity information and highly dependes on the image scale, this paper presents two improvement based on q-order moments of general dimension theory, marked D（q）. This paper proposes a new weighted calculation of boxes number method conbined intensity information by analyzing the factors affecting the probability of growth, then proposes a two-dimensional method of calculating fractal dimension based on the gride intensity and mean. Experiment shows that the new method improves features differentation, computes features more robust and more effective, and improves the classification accuracy by putting the new method in the identification systerm of blood cells.

Key words: feature extraction, malti-fractal, gride, growth proability