Intelligent Detection Method for Internal Cracks in Aircraft Landing Gear Images under Multimedia Processing

In view of the lack of image enhancement processing in the traditional methods in image preprocessing, which leads to a long detection time for internal cracks in the image and poor visual effects, an intelligent detection method for internal cracks in aircraft landing gear images under multimedia processing is proposed. A spatial index structure is established based on the multimedia database, and the aircraft landing gear images in the structure are enhanced and denoised. Image segmentation is performed according to the preprocessing results, the crack foreground and the road surface background in the image are separated, and the threshold value of each image is calculated. The threshold segmentation result is used to distinguish which pixels are the areas where the cracks may exist and which pixels belong to the image background, and the judgment result realizes crack detection. The experimental results show that the crack detection time of the proposed method is shorter, the visual effect of the detection results is better, and the average of the expert score reaches 93.6 points, which verifies the effectiveness of the proposed method from both the subjective and objective aspects.

Research on the construction of TCFL resource database system based on artificial intelligence

The teaching resource bank is very important for the education of linguistics. In the construction of teaching Chinese as a foreign language, we should first build a teaching resource library. Only in this way can we meet the requirements of the Ministry of education and achieve better teaching objectives. The purpose of the construction of teaching resources database is to make the teaching resources can be systematically and scientifically planned, stored in the computer in the form of data, and can be directly extracted from the computer when necessary, so as to realize the efficient utilization of resources. Based on the existing problems of teaching Chinese as a foreign language, this paper puts forward some suggestions on the construction of teaching resource database. In recent years, the rise of artificial intelligence technology provides a new idea for the establishment of teaching resource database. According to the basic idea of artificial intelligence, scientists have established a new database of teaching Chinese as a foreign language, updated and improved the original database, and established a new standard for teaching database according to the characteristics of artificial intelligence technology. A teaching resource database system based on teaching resources and artificial intelligence is established. The system is divided into data layer, logic layer and presentation layer. Artificial intelligence is used as a bridge connecting different parts. In the process of establishing the multimedia database of TCFL, we should develop in all aspects, and pave the way for the future research after laying a solid foundation of data.

Multimedia system and database simulation based on internet of things and cloud service platform

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.

Analisis Seleksi Tingkat Kecocokan Gambar pada MDID Multimedia Database Dengan Menggunakan Metode ImageDNA

Dengan semakin tersedianya pilihan informasi digital saat ini, definisi multimedia yang umum diterima adalah kombinasi dari berbagai media seperti teks, gambar, suara, video, animasi. Dalam teoris basisdata, multimedia basisdata mulai dikenalkan yaitu kumpulan data multimedia terkait. Basisdata yang dipilih untuk optimasi dalam penelitian ini adalah MDID (Multiply Distorted Image Database) yang terdiri dari 20 gambar referensi dan 1600 gambar yang sudah diberikan distorsi. Basidata 1600 gambar tersebut akan diuji kecocokan dengan 20 gambar referensi dengan menggunakan metode ImageDNA. Nilai ImageDNA kemudian dilakukan uji data pencilan, sehingga gambar yang nilai ImageDNAnya ekstrim akan dikeluarkan dari basisdata MDID. Hasil dari penelitian ini adalah ada 100 gambar yang dikeluarkan

A Distributed M-Tree for Similarity Search in Large Multimedia Database on Spark

In this chapter, Image2vec or Video2vector are used to convert images and video clips to vectors in large multimedia database. The M-tree is an index structure that can be used for the efficient resolution of similarity queries on complex objects. M-tree can be profitably used for content-based retrieval on multimedia databases provided relevant features have been extracted from the objects. In a large multimedia database, to search for similarities such as k-NN queries and Range queries, distances from the query object to all remaining objects (images or video clips) are calculated. The calculation between query and entities in a large multimedia database is not feasible. This chapter proposes a solution to distribute the M-Tree structure on the Apache Spark framework to solve the Range Query and kNN Query problems in large multimedia database with a lot of images and video clips.