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.

翻译：珠宝物品检索通常用于在在线市场中通过样本查询参考图像寻找用户所需商品。鉴于当前的技术进展，由于各类珠宝物品的同步性、图像或视觉流中珠宝商品的遮挡现象以及形状变形，基于内容的珠宝物品检索（CBJIR）在实际视觉搜索中仍存在局限性。本文提出了一种基于HSV色彩空间中局部区域直方图的内容驱动珠宝物品检索方法。通过五个局部区域，我们新颖的珠宝分类模块从查询图像中提取特定特征向量。该珠宝分类模块同样应用于珠宝数据库以提取特征向量。最终，通过匹配数据库与查询特征向量之间的相似度得分，从数据库中检索出珠宝物品。所提方法的性能在公开的珠宝物品检索数据集（即 ringFIR 与 Fashion Product Images 数据集）上进行了测试。实验结果表明，该方法在检索所需珠宝产品方面优于基线方法。