Fine-grained Classification Of Lung Cancer Image Based On Fusion LBP And Wavelet Moment Algorithm Research

In recent years,the continuous development of science and technology has provided a good chance for people's living standards.Especially smart phones,cameras and other advanced image acquisition equipment is ever-changing in a surprising speed in people's social life.A large number of images are generating,and people's lives are filled with all kinds of image data.The amount of image data is increasing,and the demand for the effective organization and management of these massive data is gradually generating.The ultimate goal is to realize the effective classification of image data.Strong demand attracting a large number of research scholars into research,and image classification field derived from this gradually.At the same time,the rapid development of the Internet provides strong support for the development of the field of image classification,how to reduce the cost of manual participation in the process of image classification,and increase the usage of computer into the core research content has become the new issue.From a research point of view,the computer should have such recognition and organizational skills,in the entire process of image classification to maximize the savings in labor costs.With the deepening of research,image classification technology has applied to many areas and achieved considerable research results.Especially in the field of machine vision,image classification has a pivotal position.With the development of image classification technology matures,another new research areas-fine image classification field gradually derived from it.In the process of gradual exploration of this research,the researchers found that fine image classification technology have a very wide range of practical value and research prospects in food monitoring,material analysis,ecological environment monitoring,geological survey and many other fields.So the computer vision and related fields of research scholars have put research into the image classification technology.At the same time,a lot of related technologies such as artificial intelligence technology,computer technology have been widely developed.The progress of these areas in theory and technology also promote the fine image classification technology development.But at present,the application of fine image classification in medical image classification is still relatively small.Therefore,this paper presents a complete set of algorithms to achieve the fine classification of lung cancer images,that is,lung cancer is further divided into small cell lung cancer,squamous cell lung cancer,adenocarcinoma,bronchioloalveolar cancer.This classification technology can effectively promote the further development of lung cancer diagnosis and treatment.Local Binary Pattern(LBP)is a simple and efficient texture feature extraction algorithm,which has extensive application to many popular areas,such as: face recognition,medical image processing,scene recognition classification.In this paper,we propose a fusion feature extraction algorithm based on LBP in the step of image feature extraction and integrate it into a technical framework suitable for fine classification of lung cancer images,which includes other algorithm steps for image fine classification.Finally,the whole set of algorithms is applied to fine classification of lung cancer images.The research contents of this paper are as follows:(1)This paper briefly introduces the research status of image classification and related technology,summarizes the research work of fine image classification technology,and enumerates the application of image classification technology in military and life field.(2)Introduce the fast template matching image fine classification technology which depends on the framework of this paper,mainly image preprocessing technology,image extraction technology,feature response graph and so on.(3)This paper introduces the original LBP algorithm and its related classical improvement techniques,and introduces the research status of LBP algorithm and its application in a wide range of fields.LBP has been used in general medical image classification technology in the past,but it is easy to ignore the details of the important information classification,and only the texture features can not fully represent the image information,so the application of fine classification in the field of image Doomed to be inferior.At the same time,in the application of fine classification of lung cancer images,the conventional general classification technology can not be applied in fine classification.In order to solve these problems,this paper proposes a fine classification algorithm of lung cancer based on LBP and wavelet fusion feature,which can effectively identify the details of the detailed classification of lung cancer images without the need of fast template matching between codebook and interpretation Information,to achieve the fine classification of lung cancer images,is a fine classification of ideas in the field of medical application of an attempt.(4)In this paper,the improved LBP fusion algorithm is applied to the system architecture of lung cancer image fine classification,and the classical SVM classifier is used in the experimental part to carry on the subsequent classification operation.The experimental database selects the LIDC(Lung Image Database Consortium,Imaging Database Consortium)image data set.The experimental results show that the algorithm proposed in this paper can be applied to the classification of lung cancer images.The results show that the proposed algorithm can be applied to the classification of lung cancer images.