Feature extraction of 3D Chinese rose model based on color and shape features.

Flower classification is of great importance to the research fields of plants, food, and medicine. Due to more abundant information on three-dimensional (3D) flower models than two-dimensional 2D images, it makes the 3D models more suitable for flower classification tasks. In this study, a feature extraction and classification method were proposed based on the 3D models of Chinese roses. Firstly, the shape distribution method was used to extract the sharpness and contour features of 3D flower models, and the color features were obtained from the Red-Green-Blue (RGB) color space. Then, the RF-OOB method was employed to rank the extracted flower features. A shape descriptor based on the unique attributes of Chinese roses was constructed, χ2 distance was adopted to measure the similarity between different Chinese roses. Experimental results show that the proposed method was effective for the retrieval and classification tasks of Chinese roses, and the average classification accuracy was approximately 87%, which can meet the basic retrieval requirements of 3D flower models. The proposed method promotes the classification of Chinese roses from 2D space to 3D space, which broadens the research method of flower classification.

Lack of any association between insertion/deletion (I/D) polymorphisms in the angiotensin-converting enzyme gene and digestive system cancer risk: a meta-analysis.

OBJECTIVE: To investigate the association between the gene polymorphisms of angiotensin-converting enzyme (ACE) and digestive system cancer risk. METHOD: A search was performed in Pubmed, Medline, ISI Web of Science and Chinese Biomedical (CBM) databases, covering all studies until Sep 1st, 2013. Statistical analysis was performed by using Revman5.2 and STATA 12.0. RESULTS: A total of 15 case-control studies comprising 2,390 digestive system cancer patients and 9,706 controls were identified. No significant association was found between the I/D polymorphism and digestive cancer risk (OR =0.93, 95%CI = (0.75, 1.16), P =0.53 for DD+DI vs. II). In the subgroup analysis by ethnicity and cancer type, no significant associations were found for the comparison of DD+DI vs. II. Results from other comparative genetic models also indicated a lack of associations between this polymorphism and digestive system cancer risks. CONCLUSIONS: This meta-analysis suggested that the ACE D/I polymorphism might not contribute to the risk of digestive system cancer.