Requirements for web-based integrated management systems in the production of image processing components

Greiner, Philipp; Bogatsch, Tania; Jahn, Norbert; Martins, Laurin; Linß, Gerhard; Notni, Gunther

doi:10.1117/12.2532572

Cited by 2 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the product identification based on image processing emerges as a key technique of the new retail. This technique boasts an important business application value, because it is capable of improving the retrieval efficiency of products and the level of information supervision [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Feature Extraction and Retrieval of Ecommerce Product Images Based on Image Processing

Wei¹,

Zhang²

2021

View full text Add to dashboard Cite

The new retail is an industry featured by online ecommerce. One of the key techniques of the industry is the product identification based on image processing. This technique has an important business application value, because it is capable of improving the retrieval efficiency of products and the level of information supervision. To acquire high-level semantics of images and enhance the retrieval effect of products, this paper explores the feature extraction and retrieval of ecommerce product images based on image processing. The improved Fourier descriptor was innovatively into a metric learning-based product image feature extraction network, and the attention mechanism was introduced to realize accurate retrieval of product images. Firstly, the authors detailed how to acquire the product contour and the axis with minimum moment of inertia, and then extracted the shape feature of products. Next, a feature extraction network was established based on the metric learning supervision, which is capable of obtaining distinctive feature, and thus realized the extraction of distinctive and classification features of products. Finally, the authors expounded on the product image retrieval method based on cluster attention neural network. The effectiveness of our method was confirmed through experiments. The research results provide a reference for feature extraction and retrieval in other fields of image processing.

show abstract

Section: Introductionmentioning

confidence: 99%