Research And Implementation Of The Skulls Sex And Ancestry Identification Method Based On Deep Learning

With the development of data acquisition technology and computer technology,the skull automatic identification for sex and ancestry with digital three-dimensional skulls has become a very important research topic in the fields of forensic science,anthropology,archeology and so on.Skull sex and ancestry identification methods are mainly divided into traditional identification methods and computer technology identification methods,of which traditional identification methods mainly include morphological methods and measurement methods.Because traditional methods require experts participation,manual calibration of feature points,and cumbersome measurement operations,there are problems such as strong subjectivity,large errors,and time-consuming.Computer technology is used to automatically realize the sex and ancestry identification of the skull,which not only shortens the recognition cycle,but also avoids secondary damage to the skull and improves the recognition rate.It is proposed in this paper that a skull sex identification algorithm based on the skull side contour images and convolutional neural network,and a skull ancestry identification algorithm based on the skull depth map and convolutional neural network.A prototype system is developed for skull sex and ancestry recognition.The research work in this paper mainly includes:(1)A Wide module for feature extraction in neural networks is proposed.The output result of the upper layer is passed through a 1×1 convolution kernel,and then connected to the normal convolution kernel of 3×3 size and the hole convolution kernel with k hole ratio respectively in the hybrid convolution layer.Combine the final feature with the previous1×1 feature layer on the channel.This multi-channel merge method uses a sparse matrix to convert into multiple dense matrixes for calculation to make the network quickly converge.and it is not easy to overfit.(2)Aiming at the problems of highly subjectivity and low accuracy of current skull sex ide ntification methods,a method for skull sex identification based on the lateral profile of the skull combined with a convolutional neural network is proposed.First,through a series of preprocessing of the skull data,3D models of the skull are reconstructed to obtain the side images of the 3D models.Then extract the edges of the side images to obtain the side contour image required for training.Next,the neural network SINet with Wide module is used to sex-identify the lateral contours of the complete and broken skulls.The experimental results showed that the lateral profile of the skull can represent the sex characteristics of the skull well,the accuracy rate of gender identification of intact skull was 96.5%,and the accuracy rate of four types of broken skull was 94.5%,87.5%,90.0%and 75.0%,respectively.(3)Aiming at the problem that the ancestry identification requires manual labeling of feature points and the result had low accuracy,two depth projection representations for3 D skull are proposed.For the normalized 3D skull models,two depth projection methods are proposed: local depth projection and global depth projection.The principle of the local depth projection is to establish a projection plane for the front,side,and bottom of the skull and the tangent position of the skull model,and the distance from the point to the surface as the gray value of the skull deep images to project.The principle of global depth projection is to establish a cylindrical projection surface for the skull model,setting the center axis of the cylinder to the Z axis in the Frankfurt coordinate system,and the distance from the point to the surface as the gray value of the skull deep images to project.(4)Aiming at the problems of the low degree of automation and the low accuracy rate of the current skull ancestry identification methods,a method for skull ancestry identification using deep skull images combined with convolutional neural networks is proposed.First,the depth images of the skull are obtained by two methods of depth projection proposed in this paper.Then the network ANINet for ancestry recognition is established according to the SE block and Wide modules.Finally,the two depth images were combined and input into ANINet for model training to obtain the final identification model.Experiments showed that the accuracy of the method proposed in this paper is 99.03%.(5)A skull sex and ancestry identification system was designed and implemented.A prototype system for skull sex and ancestry identification was designed according to the methods mentioned before in the paper.Experients showed that the system designed in this paper can effectively estimate the sex and ancestry of the skull.