Genetic Algorithm for Weights Assignment in Dissimilarity Function for Trademark Retrieval

Abstract. Trademark image retrieval is becoming an important application for logo registry, veri cation, and design. There are two major problems about the current approaches to trademark image retrieval based on shape features. First, researchers often focus on using a single feature, e.g., Fourier descriptors, invariant moments or Zernike moments, without combining them for possible better results. Second, even if they combine the shape features, the weighting factors assigned to the various shape features are often determined with an ad hoc procedure. Hence, we propose to group di erent shape features together and suggest a technique to determine a suitable weighting factors for di erent shape features in trademark image retrieval. In this paper, we use a supervised learning method for nding the weighting factors in the dissimilarity function by integrating ve shape features using a genetic algorithm (GA). We tested the learned dissimilarity function using a database of 1360 monochr...

• Type: Conference
• Year: 1999
• Where: VISUAL
• Authors: David Yuk-Ming Chan, Irwin King
• Keywords: Information Management, Shape Features, Trademark Image Retrieval, VISUAL 1999, Weighting Factors