Evaluation of a trademark image retrieval system

Abstract

This paper describes the evaluation of ARTISAN, a system designed to provide automatic retrieval of abstract trademark images by shape feature. The system depends for its operation on analyzing each image to characterize key shape components, grouping image regions into families which potentially mirror human image perception, and then deriving characteristic indexing features from these families. A variety of run-time search options is provided, allowing the user to select alternative sets of shape features and similarity matching paradigms.The system's retrieval effectiveness has been evaluated by measuring its retrieval effectiveness using a set of 12 real queries with known results put to a collection of over 10 000 abstract geometric shapes from the UK Trade Marks Registry. Normalized recall and precision scores averaged 0.93 and 0.65 respectively. The results suggest strongly that the basic ARTISAN approach is valid, though the present version has significant limitations, particularly when handling badly-scanned images or images with implied shape features. Possible ways of overcoming these limitations are discussed.

The User Interface & Content-Based Image Retrieval Systems

“…A recent evaluation of the systems image retrieval performance produced encouraging retrieval results despite difficulties in retrieving a relatively small number of image classes. However, these problems suggest that the current system does not yet offer reliable enough performance to form the basis of an commercial image retrieval system [33].…”

A Privacy-preserving Image Retrieval Scheme in Edge Computing Environment

“…The specific steps of each algorithm are explained below: 1)INDEX SHARE BUILD 𝑓𝑓 ̂← 𝑰𝑰𝑲𝑲𝑰𝑰𝑲𝑲𝑰𝑰𝑲𝑲𝑲𝑲𝑲𝑲(𝐼𝐼). The image owner extracts the color feature [24] of the database image 𝐼𝐼 which can be called database image feature and expressed as 𝑓𝑓 = (𝑓𝑓 1 , … , 𝑓𝑓 𝑛𝑛 ), where 𝐸𝐸 is the dimension of the feature. Then image owner generates index 𝑓𝑓 ̂= (𝑓𝑓 1 , … , 𝑓𝑓 𝑛𝑛 , ‖𝑓𝑓‖ 2…”

Hierarchy-of-Visual-Words: a Learning-Based Approach for Trademark Image Retrieval

“…The first systems to implement content-based retrieval for trademark images were developed by Kato et al [1], Wu et al [2] and Eakins et al [3]. The TRADEMARK system [1] uses the spatial distribution, spatial frequency, local correlation, and local contrast of pixel blocks as visual features.…”

“…The later includes Fourier descriptor of the shape, moment invariants, and grey level projections. ARTISAN [3] applies a structural pattern similar to STAR's and incorporates principles derived from Gestalt psychology to cope with device-only marks. Some solutions integrate global features to capture the gross essence of the shapes and local features to describe the interior details of binary trademark images.…”