关键字：Stored product pests; Image database; Obscure; Local feature extraction; Target recognition

摘要：In recent years, the target of local feature extraction and recognition technology is a hot research topic in digital image processing and computer vision field.In target recognition, pest undetected phenomenon often happens due to occlusion, once the conditions are favorable, pests quickly multiply and spread, causing great harm to the stored product.we established a common stored product pests image database, proposed feature extraction and matching algorithms, based on the combination of improved SURF and multi-resolution histogram.Pests specified in the database for target identification, especially when the pest is partially obscured, or the shape and size changes,by finding matching number of feature points the description of the target for accurate identification.This method is efficient, time-saving,provides an important scientific basis for the entry-exit inspection and quarantine in rapid identification of stored product pests.It is more conducive to the subsequent classification.

卷号：846-847

是否译文：否