The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 53-177
Full Name: ANJALI GOYAL
Position: Assistant Professor
Age: ON
Sex: Female
Address: GNIMT, MODEL TOWN, GUJARKHAN CAMPUS, LUDHIANA
Country: INDIA
Tel: +91-9914513435
Tel prefix:
Fax: 91-161-2772626
E-mail address: anjali.garg73@gmail.com
Other E-mails: goyalanjali@yahoo.com
Title of the Paper: An Analysis of Shape Based Image Retrieval Using Variants of Zernike Moments as Features
Authors as they appear in the Paper: Anjali Goyal, Ekta Walia
Email addresses of all the authors: anjali.garg73@gmail.com, wekta@yahoo.com
Number of paper pages: 18
Abstract: Zernike Moments (ZMs) have been most widely used in extracting the region based shape features of an image such as Logo, Trademark, Clip-art etc. Though ZMs are assumed to be the best descriptors, still retrieval of accurate images is an important research area. In most of the researches, emphasis is given only on magnitude of ZMs and phase component is ignored. Complex Zernike Moments (CZMs) take both Phase and Magnitude component for feature extraction. This paper describes the concept of local and global features that are used in Shape Based Image Retrieval. Global features are extracted using ZMs or CZMs. In order to capture local details of an image, variety of options are available i.e. Wavelets, Mean and Standard deviation of Centroid distance, Curvature on edged images etc. The retrieval results of global features are compared with results obtained using combined local and global features. Experiments are performed on shape database of 250 images from dif!
ferent groups taken from MPEG-7 CE-2 database. Recall – Precision and Bulls Eye Performance (BEP) are chosen as measures for retrieval performance. It is observed that a combination of local and global features i.e. Wavelets and Complex Zernike Moments (WCZMs) perform better in terms of Retrieval Accuracy without any overhead of increased feature space. Based on our experiments, WCZMs are recommended for SBIR system to achieve better retrieval accuracy. They are also robust towards blur and noisy images in addition to being rotationally invariant. Other local features like Curvature and Centroid distance with ZMs prove better in terms of retrieval accuracy against ZMs but WCZMs outperform this descriptor also.
Keywords: Shape Based Image Retrieval (SBIR); Global features; Zernike Moments (ZMs); Complex Zernike Moments (CZMs); Local features; Wavelets; WCZMs.
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