Simulated Annealing Algorithm Of Defocusing Iris Image Restoration

With the rapid development of information technology,the research oninformation security has become one of important topics.The identity recog-nition based on the biology characteristics of human body becomes more im-portant.The iris recognition is a kind of the biometrics technologies based onthe physiological characteristics of human body,compared with the featurerecognition based on the fingerprint,palm-print,face and sound etc,the irishas some advantages such as uniqueness,stability,high recognition rate,andnon-infringing etc.Hence the iris recognition technology has recently becomepopular in identity recognition.Iris collection is more important in iris recognition.The iris recognitionsystem which is proposed by Daugman has already mature greatly.But theprecondition is that recognition has to process when the iris image is clear.Because the great mass of the image sampling equipment don't have thefunction which can adjust the focus,the image that we gained is often defo-cusing.The blurry image will bring the di?culty in iris collection,so how to getthe clear image is become very important.The study of iris image restorationmeans a lot for the improvements of the speed and accuracy of subsequentrecognition algorithm.This paper aim at the study of blurred iris image.We restore the blurrediris image which is acquired by changeless focus camera.The article first provides an overview of the classical image restorationtechniques, a mathematical model is given for degraded and restoration imagesIntroduced Classical image restoration algorithm.And then we analyzed the reason that iris image is out of the focus.Owingto the variable focus equipment is very costly,now most iris image samplingequipments are fixed-focus.The image is often out of focus,for example,theout of focus because of the relative motion between a person and a cam-era;when depth of field is small,the object of di?erent depth in imaging area will cause out of focus of di?erent degree.It is an unexpected factor for out offocus to cause the faintness of iris image,the defocusing distance are alwaysunpredictable,which brings the di?culties in defocusing iris image restora-tion. Something else,there is noise during the image sampling,which e?ectsthe quantity of image.Because the information of noise is uncertain,the prob-lem of denoising is also a significant problem for iris image restoration.Thekey element of iris image restoration lies in the setting of degradation modelof blurry image,the problem of denoising and the decision of the parameterof degradation model.The parameter of degradation model in defocusing irisimage can be abstracted as a disc function,its corresponding radii of thedisc is the only the parameter of degradation model(the blur radii).The writergives a detailed illustration about the getting of this parameter.Chapter IV provides an overview of the traditional simulated anneal-ing algorithm, introduced the physical background of Simulated annealingalgorithm : Metal object is heated to a certain temperature, it's freedom ofmolecular movement in the state space, with the drop in temperature, molec-ular stay in di?erent state, molecular Tended to an orderly movement. Thishigh temperature to low temperature by cooling the heat treatment graduallybecame the annealing process. Annealing is a physical process, in the anneal-ing process of the energy system, constantly Tends to reduce the minimumvalue. An annealing process by the heating process, isothermal process andcooling process is composed of three parts. the mathematical description ofthe process of annealing and Boltzmann equation:Assuming thermodynamicsystem S in a state of D,One state i of energy for Ei, under the the temper-ature T,after a period of time to reach thermal equilibrium,Molecule in thisstate at this time to meet the Boltzmann probability distribution:Where Z (T) for the probability distribution of the standardized factor. At a high temperature, S can be in any energy state, when the SA canbe seen as carrying out wide-area search in order to avoid a local optimum;At low temperatures, S can only be in a state of smaller energy, when the SAcan be seen as doing local search, in order to facilitate the refinement of thesolution; when the temperature tends to zero infinite, S only in the energyminimization State, when the SA on the global optimal solution obtained.given the traditional simulated annealing algorithm structure and process,Finally a brief analysis of the convergence of the algorithm.The final chapter is the focus of this paper, a detailed introductionabout applications of the simulated annealing algorithm in Defocusing irisimage restoration , analysis the sick of the image restoration process: Inmathematical form That for T?1(g +ε) = f +δ,Which theεvalue for ar-bitrary small,δfor the disturbance caused by the corresponding f,when thesickδε. the energy function of simulated annealing algorithm is given:J(f) = ||Hf ? g||2 +α||Cf||2. Presented a detailed calculation of energyfunction perturbation,Gives the recursive formula: Through these recursive formula to reduce the computational complexityof the algorithm to save memory space. The experimental results show thatthis paper has made a good recovery results.