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Analysing the retinal colour fundus is a critical step before any proposed computerised automatic detection of eye disease, especially Diabetic Retinopathy (DR). The retinal colour fundus image contains noise and varying low contrast of the blood vessel against its surrounding background. It makes it difficult to analyse the proper order of the vessel's network for detecting DR disease progress. The...
Reversible data hiding is a method of hiding secret information (watermark) in some multimedia cover data in such a way that after extracting the watermark, original cover data can be recovered without any loss of information. In this paper, a novel reversible data hiding technique, based on integer-to-integer wavelet transform and histogram-bin-shifting, is proposed for medical images. Images are...
In this paper, the SIMPLIcity (Semantics-sensitive Integrate Matching for Picture Libraries), an image retrieval system is introduced. The feature extraction is based on Histogram, color layout and coefficients of wavelet transform. This retrieving system adopts feature database for matching so as to reduce the search space which is especially useful in a larger image database. Retrieval images are...
The Image segmentation is the focus in the image processing technology all the time. Medical image segmentation is an important application in the field of image segmentation. Wavelet transform is proposed to segment medical image. Firstly the gray level histogram of the medical image was processed using multiscale wavelet transform. Then the gray threshold was gradually emerged by the performance...
This paper aims to develop an efficient content - based image retrieval approach for brain image database. The combination of Cohen-Daubechies-Feauveau (CDF) 9/7 wavelet and Local Ternary Co-occurrence Patterns (LTCoP) is used for feature extraction in solving the brain image retrieval problem. The experimental dataset used for the retrievalpurpose is from OASIS - MRI database. The mean precision...
In this paper, a new contrast enhancement method is implemented to medical images by applying local range modification on shearlet coefficients. The proposed method is evaluated by the contrast improvement index(CII) and results show that the method is superior to other methods. Moreover, resulting images show that the proposed method can enhance useful features in medical images and improve the visualization...
Reversible data hiding schemes can be used to embed sensitive personal information in a generic signal without any loss of either the embedded or the host information. Multiple watermarking allows embedding different marks at different stages into the host media. This paper proposes a high capacity reversible multiple watermarking scheme for medical images based on integer-to-integer wavelet transform...
Digital radiographs play very important role in medical imaging. However, the image quality has weakness with lower contrast and some noises owing to various reasons. So it is necessary to enhance these images to facilitate the postprocessing or diagnosis. In this paper, our method utilized wavelet transform to decompose the image, removed the noise using wavelet threshold method, and modified the...
For years, researchers in medical image retrieval area have been representing and recognizing medical images based on local binary patterns (LBP). Compared to Gabor wavelets, the LBP features can be extracted faster in a single scan through the raw image and lie in a lower dimensional space, whilst still retaining image information efficiently. To improve the recognition rate, several methods using...
In this work we present an approach based on image texture analysis to obtain a description of oocyte cytoplasm which could aid the medical expert in the selection of oocytes to be used for assisted insemination. More specifically, we describe some characteristics such as different levels of uniformity and/or granularity in the oocyte cytoplasm, using multiresolution texture analysis applied to light...
This paper presents an effective statistical model for wavelet high frequency subband histograms and a novel image signature by bit-plane extractions. Our proposed model, namely, the first order correlated bit-plane probability model, is shown to match well with the observed histograms especially when the size of subband coefficients is small and performs better than the product Bernoulli distributions...
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