Sensitive Image Detection Algorithm Research

With the constant development of Internet and multimedia technology, the spread of pornographic images becomes more and more serious. In order to purify the network environment for minors to minors, create a healthy and pure cyberspace. Sensitive image identification and filtering technology has been a great deal of attention and separate the important research topic. This article analysis and research algorithms of Sensitive image recognition and filtering and gives the corresponding experimental results.The specific work is as follows:1、reviewed and summarized domestic and foreign sensitive image detection algorithms, and summarizes the technical problem of sensitive image detection algorithm2、As a result of pornographic images have a common characteristic-----a large number of bare skin. According to the color space and color model analysis, proposed a method based on image enhancement algorithm for skin color detection model, it is combined to image enhancement algorithm and double skin model, This model make up the double color in complex environment detection effect is not good and improve the detection accuracy.3、Based on the texture detection algorithm in color detection, this paper by using first order gray rectangle algorithm to detect texture, no skin and eliminates the error area of interference, extract the feature vector for the future lay the foundation.4、Due to the face image on the sensitive image detection interference, this paper joins the face detection algorithm, it can remove the face image interference and choose to face higher detection accuracy of the algorithm---Adaboost algorithm, to effectively improve the rate of face detection.5、In skin color mask, the extraction of salient region feature vector as the input of the classifier, these feature vectors including color accounted for the whole image ratio、skin for external rectangle ratio、color with the number of connected regions、the largest connected area proportion of the largest connected area、color for skin external rectangular ratio、image center color region color ratio.6、After extraction of feature vectors, then the classifier selection and design, the classification ability directly affects the performance of eroticism image recognition. In the choice of classifier, choose to solve small sample, nonlinear and high dimensional pattern recognition, classification problem has great advantages of the SVM classifier, and the experimental results are given.7、In order to further improve the classification accuracy rate, construct PSO-SVM model and GA-SVM model parameters of SVM were optimized, and the two kind of model of Matlab simulation experiment, the experimental results show that, these models than to simply use a SVM detection effect especially accuracy is greatly enhanced, reached anticipated goal.