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Lung cancer is the most common fatal malignancy in both men and women. Early detection and treatment of lung cancer can greatly improve the survival rate of patient. The present work describes the design and development of a two stage computer-aided diagnosis (CAD) system that can automatically detect and diagnose histological images such as CT scan of lung with a nodule into cancerous or non-cancerous...
Abstract- Newer generations of diagnostic machines are based on digital technologies for data acquisition and consequently with the emergence of digital archiving systems for preservation of diagnosis is rapidly increasing. The goals of Content-Based Image Retrieval (CBIR) systems is to process on collections of images, extract features and based on visual queries, extract relevant image from a repository...
Image retrieval is an active research area in numerous applications. Color and Texture is an important Low Level features for content based image retrieval and this paper proposes a method for extracting color feature using Discrete Wavelet transform and Auto-Correlogram. The Weighted Wavelet Auto-Correlogram is applied on the High frequency sub bands such as LH, HL and HH of the Y, Cb, and Cr channel...
Compression artifacts are the results of an aggressive data compression scheme applied to an image that discards some data which is determined by an algorithm to be of lesser importance to the overall contents but which is nonetheless discernible and objectionable to the user. In this paper we present a post-processing algorithm that focuses on restoring the clarity of important image features and...
Image resolution enhancement is a usable process for many image processing applications such as geoscience studies, astronomy and geographical information systems. One of the traditional methods used to increase the image resolution is image interpolation but the potential problem associated with it is to magnify the image many times without loss in image clarity. However, all the classical linear...
In the pixel based multiscale Markov random field(MRF) model, a sequence of MRF was hierarchically defined on the multiple spatial resolutions which might suffer from the deficiency of modeling the large range of interaction. In order to overcome such a problem, we attempt to introduce the region based multiscale MRF model, in which hierarchical MRF model is defined over multiresolution image segmented...
A weld pool image processing algorithm based passive-light-vision has been studied in this paper. Firstly, we have designed a kind of method to directly capture the welding pool images of Gas Metal Arc Welding (GMAW) by a CCD camera with a narrowband filter. Next, using the median filter and wavelet transform eliminates noise and keeps the details of the image effectively. Then, we have proposed to...
This paper describes the detection of rust defects on highway steel bridges, which are one of the most commonly observed defects on coating surfaces and thus have to be taken care of appropriately since they severely affect the structural integrity of bridges. A rust defect assessment method is presented that automatically detects the percentage of rust in a given digital image of bridge surface taken...
Contourlet transform is the combination of the multi-scale analysis and multi-directional analysis in processing high-dimensional signals and has better approximation precision and better sparse description. Firstly, Using the Contourlet transform, several polarimetric images can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions. For...
Medulloblastoma (MB) is the most common brain tumor in children. There are four distinct subtypes of MB, but patients with anaplastic/large cell have the worst prognosis. Since the morbidity is highly correlated with treatment for MB, the ability to distinguish aggressive (such as anaplastic/large cell) MB is crucial. We present a scheme that leverages quantitative image texture features (Haar, Haralick,...
The fusion of images captured from multi-modality sensors has been studied for many years. It is aiming at combining multiple sources together to maximize the meaningful information and reduce the redundancy. Meanwhile, sparse representation of images has been attracting more and more attentions. It has been effectively utilized on image reconstruction, image de-noising, super-resolution and others...
Image edge detection plays an important role in the system of computer vision. Wavelet is a powerful tool in image processing and has wide application to edge detection for its multiscale characteristic. Based on wavelet modulus maximum edge detection algorithm, an improved method is proposed in this paper, which gives an automatic determination function of eliminateing noise threshold by using the...
In this paper, different types of speckle noise and impulse noise removal techniques are presented. Dual Tree complex wavelet transform because of having time and frequency resolution (MRA) and also of its shift invariance property works well in removing the speckle noise. Because of adaptive nature of mask size depending on the noise quantity in the image, adaptive median filter works better in removing...
This paper presents an multiscale image retrieval algorithm which uses a new class of image features as the image descriptors, from the DTCWT(Dual-Tree complex wavelet transform). It uses DTCWT to detect keypoints, make feature vectors which are invariant to image scaling, translation and rotation as similar as SIFT(Scale Invariant Feature Transform) feature, compare the similarity of the features...
Steganography is used to hide a secret message within a cover image, thereby yielding a stego image such that even the trace of the presence of secret information is wiped out. The purpose of steganography is to maintain secret communication between two users. Steganography has several technical challenges namely high hiding capacity and imperceptibility. In this paper we propose a modern steganographic...
In order to overcome the lacking of Shift invariance in Contourlet Transform, enable the image fusion to be in accord with human vision properties, Nonsubsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Networks(PCNN) were used jointly in image fusion algorithms. Original images were decomposed to get the coefficients of low frequency sub bands and high frequency sub bands. The coefficients...
The fire and smoke monitoring systems are useful in different industry such as military, social security and economical. The recent methods for fire and smoke detection are used only motion and color characteristics thus many wrong alarms are happening and this is decrease the performance of the systems. This research presents a new method for fire and smoke detection through image processing. In...
Modern multislice computed tomography (CT) scanners produce isotropic CT images with a thickness of 0.6 mm. These CT images offer detailed information of lung cavities, which could be used for better surgical planning of treating lung cancer. The major challenge for developing a surgical planning system is the automatic segmentation of lung lobes by identifying the lobar fissures. This paper presents...
In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is...
We present a new graph-based transform for video signals using wavelet lifting. Graphs are created to capture spatial and temporal correlations in video sequences. Our new transforms allow spatial and temporal correlation to be jointly exploited, in contrast to existing techniques, such as motion compensated temporal filtering, which can be seen as "separable" transforms, since spatial and...
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