  Jewellery item retrieval is regularly used to find what people want on online
marketplaces using a sample query reference image. Considering recent
developments, due to the simultaneous nature of various jewelry items, various
jewelry goods' occlusion in images or visual streams, as well as shape
deformation, content-based jewellery item retrieval (CBJIR) still has
limitations whenever it pertains to visual searching in the actual world. This
article proposed a content-based jewellery item retrieval method using the
local region-based histograms in HSV color space. Using five local regions, our
novel jewellery classification module extracts the specific feature vectors
from the query image. The jewellery classification module is also applied to
the jewellery database to extract feature vectors. Finally, the similarity
score is matched between the database and query features vectors to retrieve
the jewellery items from the database. The proposed method performance is
tested on publicly available jewellery item retrieval datasets, i.e. ringFIR
and Fashion Product Images dataset. The experimental results demonstrate the
dominance of the proposed method over the baseline methods for retrieving
desired jewellery products.
