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There have been significant progresses in single image super-resolution (SR) using deep convolutional neural network. In this paper, we propose a modified deep convolutional neural network model incorporated with image texture priors for single image SR. The model consist of a particular feature extraction layer followed by image reconstruction process, aiming to centralize on the image texture information...
In a complicated cloud storage environment in which users upload a large number of files everyday, in order to better solve the challenge of inefficient malicious detection and weak adaptability of multi-platform detection in the traditional way, we propose a malicious file detection method which is based on image texture analysis and BP neural network algorithm. By combining the technology of image...
Regarding texture features, Local-based methods such as Local Binary Pattern (LBP) and its variants are computationally efficient high-performing but sensitive to noise, and suffering global structure information loss. By contrast, filter-based counterparts, the Scattering Transform for instance, are tolerant to noise and translation but often lack of small local structure information. In this paper...
A statistical classification method using Mel cepstrum and image texture is introduced to passive sonar target recognition. Image texture features are extracted by regarding Mel frequency cepstrum coefficients (MFCC) as a digital image. Bayesian formula and Markov chain are applied to the recognition algorithm. The classification experiments are carried out for three different kinds of targets based...
The detection and localization of the optic disc in retinal images is an important step in the diagnosis of ocular diseases and many works with this thematic area were presented over the years. In the current paper we develop a method to accurate detection of the optic disc which combines LBP techniques and features extracted from co-occurrence matrix on color channels. Two classifiers were used to...
In this paper, we present two approaches of the image texture pretreatment. The reason behind it is to reduce the number of the grey level in the image, by assigning to each pixel a value that characterizes the local information of the neighborhood of this same pixel. This coding process will allow us to reduce the size of the co-occurrence matrix and also minimize the extraction time of Haralick...
Images texture extraction is a core step in image pattern recognition applications such as paper texture identification or fingerprinting. Different methods are applied for paper images texture extraction. Subsequently, one of the well-known methods in images texture extraction is the Locale Binary Pattern (LBP) method. However, the LBP method show a number of drawbacks in paper images texture extraction...
Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. The therapeutic goals of UC are to first induce and then maintain disease remission. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms associated with UC, and large variations...
Glaucoma disease detection from retinal images using classifiers like Least Square-Support Vector Machine classifier, Random forest, Dual Sequential Minimal Optimization classifier, Naive bayes classifier and Artificial neural networks. The textual features obtained from retinal images are used for this classification. Energy distributions over wavelet sub bands provide these features. The proposed...
Growth of the image mining arena calls for the need of quality image retrieval techniques in par with the human perception which are invariant to scale and rotation. An optimized content based image retrieval system based on local visual attention features to bridge the semantic gap problem is proposed. The approach involves the salient point detection using Scale Up Robust Features (SURF) detector...
Glaucoma disease detection from retinal images using classifiers like least square-Support Vector Machine classifier, random forest, dual Sequential Minimal Optimization classifier, naive bayes classifier and artificial neural networks. The textual features obtained from retinal images are used for this classification. Energy distributions over wavelet sub bands provides these features. The proposed...
Over 100 million cargo containers that are declared empty on their manifests are transported globally each year. Human operators can confirm if each is truly empty by physical inspection or by examination of an X-ray image. However, the huge number transported means that confirmation is far from complete. Thus, empty containers offer an opportunity for criminals to smuggle contraband. We report an...
Purpose:To investigate the feasibility of utilizing texture features to classify nodule from normal thyroid tissue in Computed Tomography (CT) images. Materials and Methods: Group A (negative) includes 152 normal thyroid CT images from 55 patients healthy controls enrolled in the study. Group B (positive) includes 134 thyroid images with nodules (50 malignant, 84 benign) of 58 patients undergone thyroid...
The technique of 3D scene reconstruction from 2D scene image can satisfy the demands of 3D display market, and it is the main research contents in the field of image processing. For the 3D reconstruction, the extraction of depth cues is one of the most important contents. Therefore, we proposed a least-square depth estimation method based on multi-scale texture features, which can better describe...
Splicing is a very common operation performed for image forgery. It involves merging of two or more different images to form a combined image that is significantly different from the original image. In this paper an image splicing detection method based on texture features of spliced image is proposed. The proposed approach calculates grey level run length matrix (GLRLM) texture features for the forged...
Emotion recognition has been an important research topic in the area of human computer interaction (HCI) for different application, in the last decade for instance proper emotion recognition has a wide range of applications in security, entertainment, and training. Emotion is expressed via facial muscle movements, speech, body and hand gestures, and various biological signals such heart rate. This...
Night video surveillance is crucial to construct an all-weather video surveillance system. However, night video surveillance faces several problems: no color information, low brightness, low contrast, and low signal to noise ratio (SNR). These problems can introduce serious false and missing object detections. In this paper, we propose a novel night video surveillance method based on the image second-order...
The flotation froth surface texture can be used as an indication to illustrate the production states. A novel froth image texture extraction and classification method based on complex network is presented to obtain the accurate texture features descriptors and facilitate the mineral flotation process monitoring. Firstly, froth images are pre-classified by defining a similarity coefficient. Then, designing...
Wavelet Transforms is a part of large community of mathematical function approximation method, they are being increasing and being deployed in image processing for segmentation, filtering, classification etc. This work is based on image classification with the use of single level Discrete Wavelet Transform (DWT). Wavelets have been employed in many applications of signal processing. The texture features...
With the development of information technology in biomedical signal detection, processing and digital image signal processing, the role of automatic visual recognition becomes more important. In this paper, in order to effectively extract the feature information of human viruses (HV) microscopic images, an algorithm of HV microscopic image feature extraction and recognition using gray level co-occurrence...
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