Design and Realization of Computer Image Intelligent Recognition System

The application of intelligent image recognition technology in life is more and more extensive, especially in the field of computer and multimedia, the research of machine vision system is becoming more and more mature, and the demand of human society for information processing is constantly increasing. This article first analyzes the basic knowledge of digital images based on computer technology, including basic knowledge of digital images, basic knowledge of image filtering and image recognition algorithms. Secondly, this paper studies the design and implementation of computer image intelligent recognition system.

Research on Intelligent Processing Technology of Computer Image Recognition Based on Machine Vision

Although computer image recognition can distinguish very clear images, it is only limited to a certain number of years. Or it can only be clearly distinguishable from some range of graphs, and expanding the range or changing the range will not achieve the state that people want it to achieve. Nowadays, China’s equipment in this field can only conduct activity research in the two-dimensional space, and can only decompose and analyze the two-dimensional pictures. For high-dimensional and complex graphs, they still cannot be processed and the processing requirements are not up to standard. Moreover, the development of this technology is also affected by many human factors. The operation and implementation of this technology mainly rely on the high-energy and powerful processing power of the big data computing system. If we want to ensure the quality of image processing is very good, we must closely combine the recognition image and the related technology of the computer, and do not separate from each other. In this paper, the development of the technology from the status quo, the development of the principle and characteristics of the development of the technology for an in-depth study of the technology, but also the development prospect of the technology is described.

Research on the Involvement of Computer Graphics Algorithms in Systems for the Creation of Public Sculpture

Currently, there is less research on how to improve the efficiency of the application of computer graphics technology in the creation of public sculpture. Therefore, this paper will focus on how computer graphics algorithms can enable systems for the creation of public sculpture with the intervention of computer graphics technology to create more accurate and completed works of public sculpture. It will explore and analyze how computer image algorithms can help creators apply computer image technology to finish complete and accurate public sculptures, and individual studies, computer imagery, and model analysis are also used. In systems for the creation of public sculpture, the point cloud data of the model is obtained through 3D laser scanning technology; then the algorithm of the point cloud model is integrated and the Statistical Outlier Removal algorithm of the point cloud model intervention is processed. By this way, the point cloud model of the work is optimized, and then a more completed and accurate public sculpture work can be produced by 3D sculpting or 3D printing. The research shows that, in the creation of public sculptures with the intervention of computer graphics technology, the computer graphics algorithm acquires the basis of the high-definition public sculpture data model. The computer graphics algorithm improves the accuracy and completeness of the creator using computer graphics technology; it is also the key to transform the accurate enlargement and transformation of the sculptural model into the actual sculptural work.

Prognostic Value and Computer Image Analysis of p53 in Mantle Cell Lymphoma

Background: P53 has different prognostic cut-off values in different mantle cell lymphoma (MCL) studies, and p53 immunohistochemistry (IHC) interpretation is still based on semiquantitative estimation，which might be inaccurate. This study aimed to investigate the optimal cut-off value of p53 for predicting prognosis and the possibility of computer image analysis identifying the positive rate of p53 in patients with mantle cell lymphoma (MCL). Methods: We used QuPath software to determining the p53 positive rate and compared it to the data obtained by manual counting and semiquantitative estimation. Using Youden index and Kaplan-Meier survival curve analysis, we generated survival curves. Chi-squared (χ2) test was used to compared MCL cell morphology with p53. Spearman rank correlation test and Bland-Altman analysis were used to compared manual counting, computer image analysis and semiquantitative estimation.Results: The optimal cut-off value of p53 for predicting prognosis was 20% in MCL patients. Patients with p53 ≥ 20% had a significantly worse overall survival (OS) compared to p53 < 20% (P < 0.0001). MCL patients with blastoid/pleomorphic variant cell morphology had more p53 ≥ 20% than classical type (P < 0.0001). And a strong correlation between computer image analysis and manual counting p53 in the same areas in MCL patients (spearman's rho = 0.966, P < 0.0001). Conclusions: MCL patients with p53 ≥ 20% have a shorter OS, and a blastoid/pleomorphic variant tendency. Computer image analysis could reflect the actual positive rate of p53 and is a more attractive alternative than semiquantitative estimation in MCL.

Fossil illustrations in three dimensions: Ward’s models at Cornell University

ABSTRACT Some fossil examples are rare, but the educational value of such samples is undeniable. One way around this dilemma, and one that was popular in the late 1800s and early 1900s, was to have students study 3-D models; this solution was used by many universities, among them Cornell University. One of the main, but not the only, suppliers of such models was Ward’s Natural Science Establishment of Rochester, New York, USA, which was founded in 1862 by Henry Augustus Ward (1834–1906). Even today the use of virtual, computer-generated 3-D models in classroom laboratories indicates how important 3-D visualization continues to be. But a computer image cannot be held in one’s hands, so the use of 3-D printer technology allows students to create their own physical models. However, none of these technologies can totally replace seeing and working with actual specimens or life-sized reproductions. Thus, museum displays are still an important aspect of educational activity for both students and the general public. This chapter explores how Cornell University made use of the models purchased from Ward’s in the late 1800s and the fate of some of these replicas.