Image Retrieval Using Morphological Granulometry and Dynamic Partial Function

• Main Authors: Pei Jun Yan, 顏佩君
• Other Authors: Yuang-Cheh Hsueh
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/19549945376942055912

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 94 === In recent years, there is an explosive growth of multimedia data. How to develop techniques for storage, browsing, indexing, and retrieval them efficiently is a significant issue. There are many researches on image retrievals, but very few usage of mathematical morphology which is impressive because of making real-time applications possible. Our goal is to improve precisions of morphological primitives which was introduced by J.S.Wu and propose another morphology operator: morphological granulometry as an image feature. From experimenal results, image retrieval using morphological primitives with dynamic partical function have improvement up to 30%. On the other hand, granulometric histogram has better precisions than those of color histogram, color moment primitives, and morphological primitives in most cases.