Performance evaluation of image retrieval using Enhanced 2D Dual Tree Discrete Wavelet Transform

Author(s):  
J. Leeja ◽  
P. M. S. Godwin
2018 ◽  
Vol 42 (3) ◽  
Author(s):  
Rehan Ashraf ◽  
Mudassar Ahmed ◽  
Sohail Jabbar ◽  
Shehzad Khalid ◽  
Awais Ahmad ◽  
...  

Author(s):  
SAEID BELKASIM ◽  
XIANYU HONG ◽  
O. BASIR

Image retrieval plays an important role in a broad spectrum of applications. Contentbased retrieval (CBR) is one of the popular choices in many biomedical and industrial applications. Discrete image transforms have been widely studied and suggested for many image retrieval applications. The Discrete Wavelet Transform (DWT) is one of the most popular transforms recently applied to many image processing applications. The Daubechies wavelet can be used to form the basis for extracting features in retrieving images based on the description of a particular object within the scene. This wavelet is widely used for image compression. In this paper we highlight the common features between compression and retrieval. Several examples are used to test the DWT retrieval system. A comparison between DWT and Discrete Cosine Transform (DCT) is also made. The retrieval system using DWT requires preprocessing and normalization of images, which might slow down the retrieval process. The accuracy of the retrieval using DWT has been significantly improved by incorporating efficient K-Neighbor Nearest Distance (KNND) measure in our system.


In today’s era use of digital media is most popular way of communication. Digital media covers images, videos and animations available online. The easy methods of accessing, copying and editing digital media have made them more popular. With several advantages these easy methods of copying and editing data have created some big issues like ownership identification. This increases the demand of protecting online digital media. Watermarking is solution of such problem. In this work, a block-based method has been proposed for video watermarking that uses a key at the time of embedding and extraction. Some frames are selected from the video according to a key. Watermark is embedded on the selected frames after dividing into parts called blocks. Each part of the watermark is embedded in one selected frame of the video. This method increases the security of the system as the complete watermark cannot be extracted without knowing the positions of watermarked frames and the position of the block in that frame. Watermarking is performed in the Discrete Wavelet Transform domain after scaling of watermark data. To show the authenticity of proposed scheme various attacks are applied on different watermarked video frames and extracted watermark results are shown under different tables.


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