The Study Of Seal Feature Extraction Technology Based On The Vein

Seal Identification has been a comparatively difficult thesis. It is done by hand in the bank at present, which is checking on the seal that customers left with the original seal through the manual folding. Its shortcomings are many personal factors, bad accuracy and low efficiency. It can be improve for seal's accuracy and reliability to carry out the seal administration and identification electronic, automated, intellectualized, which can prevent effectively making use of fake seal to commit a defrauding crime.Firstly, the paper has introduced the relevance theory of image identification and characteristic extract, which is the theory basis. Secondly, complete the total design of seal identification. Based on the seal pretreatment, we study the design and calculation of vein characteristic extract and distinguish the seal feature abstracted using the neural networks discriminant, which is to distinguish whether the seal is truth or false.In this paper, we analyse the characteristic of guarding against false seal, From the image vein and the analytical angle, we compare with the vein characteristic abstracts and the characteristic parameter chose and design a seal Identification system based on seal vein. Pretreatment stage: Make use of middle value wave filter the image noise, adopt carved technology based on the colour seal image to carve the seal image from the background. Base on this, we carry our the value two here and carve up out the minimal area containing seal area with border outline extract. Extract a stage in the characteristic: We extract the entropy, energy, inertia distance, part balance, correlativity on seal vein. Stage mating in the pattern: Make use of network thought BP to designe a real BP neural networks. Carry out truth or false verification on seal image after the sample trained.Our data suggested that the vein characteristic can be extracted exactly using this method. After linking the neural network, we experiment the samplet on hand, we can distinguish most seal except individual illegibility sample. The algorithm is simple and verified. The data indicate this method which is distinguishing seal from the new angle and have brought a new approach to distinguish seal. The method can prevent effectively making use of fake seal to commit a defrauding crime.