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In order to improve the working performance of cassava harvester, structural bionic design for its digging shovel was conducted. Taking the oriental mole cricket's paws as bionic prototype, a new structural bionic design method for digging shovel was established, which considers the morphology-configuration-function coupling bionic. A comprehensive performance comparison method was proposed, which is used to select the bionic design schemes. The proposed bionic design method was used to improve digging shovel structure of a digging-pulling style cassava harvester, and nine bionic-type digging shovels were obtained with considering the impact of soil mechanics. After conducting mechanical properties comparative analysis for bionic-type digging shovels, the bionic design rules were summed up, and the optimal design scheme of digging shovel was obtained through combining the proposed comprehensive performance comparison method with Analytic Hierarchy Process (AHP). Studies have shown that bionic design method not only can improve the overall mechanical properties of digging shovel, but also can help to improve the harvesting effect of cassava harvester, which provides a new idea for crops harvesting machinery's structural optimization design.

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This paper is focus on the analysis of the ability of iris segmentation method to process images with heterogeneous characteristics, simulating the dynamics of a non-cooperative environment. Aimed to improve the performance of iris segmentation method in non-cooperative environment, the authors introduce a new method. According to the different characteristics of the inner border and outer border of the iris, this new method segments iris by two steps: one step for inner border based on simple intensity operator, and the other step for outer border based on border recognition with support vector machine classifier. The performance of the proposed method and three selected traditional methods had been tested on the UBIRIS database. Compared with the traditional methods, the proposed method has more exactly accurate and less computation time on the image with poor quality. Also, the proposed method is higher robustness and less dependent on iris image conditions.

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