Details

Autor(en) / Beteiligte

• Belarbi, Mohammed Amin
• Mahmoudi, Said
• Belalem, Ghalem
• Mahmoudi, Sidi Ahmed

Titel

Web-based multimedia research and indexation for big data databases

Ist Teil von

• 2017 3rd International Conference of Cloud Computing Technologies and Applications (CloudTech), 2017, p.1-7

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

IEL

Beschreibungen/Notizen

• Indexing images represents a necessary tool for various domains related to computer vision such as video surveillance and movements analysis. Visual characteristics of image such as color, texture, shape are used to identify the content of these frames. The high increase of data (Big Data) makes us face a problem of curse of dimensionality. In this paper, we propose a cloud-based technique for images indexing images using PCA (Principal component analysis) and a binary tree. Our work consists of exploiting SIFT (Scale Invariant Feature Transform) and SURF (Speeded up Robust Features) descriptors as frames features, PCA as dimensionality reduction method of SIFT and SURF features and the binary tree representation of these images in order to accelerate the research phase and reduce the storage space. Our approach consists of developing a system based on three phases: indexing images with SIFT and SURF features, compression within the application of PCA and finally the image retrieval in the cloud.