Статьи журнала - International Journal of Image, Graphics and Signal Processing
Все статьи: 1056
Segmentation of Medical X-ray Bone Image Using Different Image Processing Techniques
Статья научная
Accurate medical image processing plays a crucial role in several clinical diagnoses by assisting physicians in timely treatment of wounds and mishaps. Medical doctors in the hospitals generally rely on examining bone x-ray images based on their expertise, knowledge and past experiences in determining whether a fracture exist in bone or not. Nevertheless, majority of fractures identification methods using X-rays in the hospitals is beyond human understanding due to variation in different attributes of fracture and complication of bone organization thereby making it difficult for doctors to correctly diagnose and proffer adequate treatment to patient ailments. The need for robust diagnostic image processing techniques for image segmentation for different bone structures cannot be overemphasized. This research implemented different image segmentation techniques on a bone x-ray image in order to identify the most efficient for timely medical diagnosis. Also, the strength and weaknesses of the diverse segmentation techniques were also identified. This will empowered researchers with appropriate knowledge needed to improve and build better image segmentation models which doctors can use in handling complex medical image processing problems. Also, miss rate in bone X-rays that contains multiple abnormalities can be lowered by using appropriate image segmentation techniques thereby improving some of the labor intensive work of medical personnel during bone diagnosis. MATLAB 9.7.0 programing tool was used for the implementation of the work. The results of X-ray bone segmentation revealed that active contour model using snake model showed the best performance in detecting boundaries and contours of regions of interest when used in segmenting Femur bone image than the other medical image segmentation approaches implemented in the work.
Бесплатно
Segmentation of Pre-processed Medical Images: An Approach Based on Range Filter
Статья научная
Medical image segmentation is a frequent processing step. Medical images are suffering from unrelated article and strong speckle noise. In this paper, we propose an approach to remove special markings such as arrow symbols and printed text along with medical image segmentation using range filter. The special markings are extracted using Sobel edge detection technique and then the intensity values of the detected markings are substituted by the intensity values of their corresponding neighborhood pixels. Next, three different image enhancement techniques are utilized to remove strong speckle noise as well enhance the weak boundaries of medical images. Finally range filter is applied to segment the texture content of different modalities of medical image. Experiment is conducted on ImageCLEF2010 database. Results show the efficacy of our proposed approach which lead to have precise content based medical image classification and retrieval systems.
Бесплатно
Segmentation of abnormal blood cells for biomedical diagnostic aid
Статья научная
The aim of our work is to obtain a maximum rate of recognition of abnormal (cancerous) blood cells. We propose the development of a system based on k-means methods, after an RGB channel decomposition by applying the algorithm which can segment our microscopic medical images. It turns out that the proposed system shows better segmentation and classification for the identification and detection of leukemia. The experimental results obtained are very encouraging, which helps hematologists to monitor the evolution of cancerous blood cells and make a good diagnosis.
Бесплатно
Segmentation of the herniated intervertebral discs
Статья научная
This paper presents two segmentation algorithms for MR spine image segmentation helping in on time diagnosis of the spine hernia and surgical intervention whenever required. One is level set segmentation and another one is watershed segmentation algorithm. Both of these methods have been widely used before (Aslan, Farag, Arnold and Xiang, 2011) (Pan, et al., 2013) (Silvia, España, Antonio, Estanislao , and David, 2015) (Erdil, Argunşah, Ünay and Çetin, 2013) (Claudia. Et al, 2007). In our approach we have used the concept of variational level set method along with a signed distance function and is compared with the watershed segmentation which we have already implemented before on a different dataset (Hashia, Mir, 2014). In order to check the efficacy of the algorithm it is again implemented in this paper on the sagittal T2-weighted MR images of the spine. It can be seen that both these methods can become very much valuable to help the radiologists with the on time segmentation of the vertebral bodies as well as of the intervertebral disks with relatively much less effort. They both are later compared with the golden standard using dice and jaccard coefficients.
Бесплатно
Статья научная
Image segmentation plays the significant roles in image processing, computer vision and as well as in pattern recognition. The Segmentation process subdivides an image into its constituent parts or objects, such that level of subdivision depends on the problem to be solved. The aim of image segmentation is partitioning an image within homogeneous regions that are significantly meaningful concerning some characteristics like intensity or texture. Based on clustering, a large number of researches have been done in the area of image segmentation. This paper presents an efficient image segmentation method in which the self organizing feature map (SOFM) is used for initial segmentation. After the initial segmentation, the segmented image is used by the K-means algorithm for further segmentation. Finally, the procedures for automatic splitting and merging the cluster are applied to obtain the appropriate number of segments in segmented image and as well as better segmented results. For analyzing the performance, we calculate the statistical measure named as Davies-Bouldin index (DB-index). The observation shows that, this method gives the better segmented results compared with K-Means algorithm, linear discriminant analysis (LDA) and K-Means based image segmentation method and also SOFM and K-Means based image segmentation approach.
Бесплатно
Self-supervised Model Based on Masked Autoencoders Advance CT Scans Classification
Статья научная
The coronavirus pandemic has been going on since the year 2019, and the trend is still not abating. Therefore, it is particularly important to classify medical CT scans to assist in medical diagnosis. At present, Supervised Deep Learning algorithms have made a great success in the classification task of medical CT scans, but medical image datasets often require professional image annotation, and many research datasets are not publicly available. To solve this problem, this paper is inspired by the self-supervised learning algorithm MAE and uses the MAE model pre-trained on ImageNet to perform transfer learning on CT Scans dataset. This method improves the generalization performance of the model and avoids the risk of overfitting on small datasets. Through extensive experiments on the COVID-CT dataset and the SARS-CoV-2 dataset, we compare the SSL-based method in this paper with other state-of-the-art supervised learning-based pretraining methods. Experimental results show that our method improves the generalization performance of the model more effectively and avoids the risk of overfitting on small datasets. The model achieved almost the same accuracy as supervised learning on both test datasets. Finally, ablation experiments aim to fully demonstrate the effectiveness of our method and how it works.
Бесплатно
Semi-fragile Image Watermarking Algorithm Based on Region-Segmentation
Статья научная
In order to improve the invisibility and the robustness of semi-fragile watermarking, the paper first brings up the idea which embedding watermark based on the attacks’ characteristic, brings forward the region segmentation operator and the image-segmentation embedding method, puts forward the characteristic and its representation in DWT transform domain based on visual features model, and brings forward the quantized central limit theorem which applies to adjusting the coefficients in general transform domain. These all make semi-fragile watermarking embedded through dynamic quantization achieve the greatest robustness. It gives wavelet transform domain coefficient redressal operator and the best restoration probability of the pixel value adjusting in experiments when the images were under attack. It leads up to a better invisibility of carrier image, a better robustness to the image processing, such as JPEG compression, noise adding, filtering, and the larger amount of embedded information. What’s more, it can ascertain the position of vicious attack exactly.
Бесплатно
Serial digital color image watermarking using composite scheme
Статья научная
Digital watermarking is one of the ways to have Copyright protection for digital information. The digital watermarking scheme used for watermark embedding has to satisfy robustness property to ensure the security of the secret information hidden. The scheme presented here will support the above said statement significantly. We propose here the scheme as composition of both blind and non-blind digital watermarking technique in a process of serial watermarking. A secret binary image is embedded in the first cover image to get first watermarked image by using blind watermarking technique. Then this first watermarked image is again embedded into second cover image to get serial watermarked image using non-blind watermarking technique. To extract secret binary image, first non-blind watermark extraction technique and then blind watermark extraction techniques are used. From this composite approach and serial watermark embedding procedure, we achieved considerable fidelity and robustness against - Rotation, JPEG compression and for noises Salt & pepper, Gaussian, Speckle, Poisson and multiple noises.
Бесплатно
Shadow Image Processing of X-Ray Screening System for Aviation Security
Статья научная
The aviation security is an important component of aviation safety providing. One of the main goals of aviation security service is to detect dangerous and prohibited objects during passengers and baggage screening. For this purpose, aviation security personnel use various equipment: X-ray screening system, body-scans, metal detectors, moving ions detectors, explosive trace detectors. The X-ray screening system gives information on internal structure of baggage. The main disadvantage of X-ray screening system is rather high level of the false alarm probability. This requires developing new methods of image processing and recognition of dangerous and prohibited objects on the background of other objects. This article develops the principles of shadow image processing while screening the baggage using X-ray system to fix the mentioned disadvantage. The math equation for shadow image is obtained based on the laws of geometry and Beer-Lambert equation taking into account the chosen scanning technique. Based on this, the article is focused to the analysis of simple objects images and their application for complex objects recognition. The article discusses the example of handgun recognition using a new approach based on spectral analysis of developed shadow images. The results of the research can be used for improvement of algorithmic toolkit in aviation security automatic decision-making system while screening the baggage by X-ray equipment.
Бесплатно
Signal propagation analysis at 28GHz and 73GHz millimeter wave bands for next generation networks
Статья научная
Fifth generation (5G) mobile networks demand large bandwidth with the explosive growth of data driven applications. This necessitates enormous amount of spectrum in the Millimeter wave (mmWave) bands to greatly enhance the communication capacity. The mmWave band offers the potential for high-bandwidth communication channels in cellular networks. Relative to conventional networks, dense mmWave networks can achieve both higher data rates and comparable coverage. The paper presents the performance analysis of mobile networks in terms of propagation path loss, coverage probability and data rates for different mm wave operating frequencies of 28GHz and 73GHz. A scenario of multi-users in a micro cell is considered in different environments i.e. rural, sub urban and urban regions and the performance parameters in each case are analyzed. Millimeter wave cellular networks at 28GHz offer less rain attenuation compared to 73GHz and is useful for next generation communications with enhanced data rates and coverage.
Бесплатно
Signature based Document Image Retrieval Using Multi-level DWT Features
Статья научная
Automatic signature extraction from document image and retrieval has a large number of applications such as in business offices, organizations, institutes and digital libraries. Hence it has attracted a lot of researchers from the field of document image analysis and processing. This paper proposes a method for automatic signature extraction and signature based document image retrieval using multi-level discrete wavelet transform features. Since the distance measures play a vital role in pattern analysis, classification and clustering, in this paper we also compared the results of retrieval using 7 distance metrics such as Euclidean, Canberra, City-block, Chebychev, Cosine, Hamming and Jaccard. Results obtained in this paper shows that city-block distance with multi-level DWT features outperforms the other 6 distance metrics used for comparison.
Бесплатно
Significance of source information for text dependent speaker verification
Статья научная
This work focuses on text dependent speaker verification system where a source feature specifically residual Mel frequency cepstral coefficients (RMFCC), has been extracted in addition to a vocal tract system feature namely Mel frequency cepstral coefficients (MFCC). The RMFCC features are derived from the LP residuals whereas MFCC features are derived from the cepstral analysis of the speech signal. Thus, these two features have different information about the speaker. A four cohort speaker’s set has been prepared using these two features and dynamic time warping (DTW) is used as the classifier. Performance comparison of the text dependent speaker verification model using MFCC and RMFCC features are enumerated. Experimental results shows that, using RMFCC feature alone do not give satisfactory results in comparison to MFCC. Also, the system’s performance obtained using the MFCC features, is not optimum. So, to improve the performance of the system, these two features are combined together using different combination algorithms. The proposed lowest ranking method yields good performance with an equal error rate (EER) of 7.50%. To further improve the efficiency of the system, the proposed method is combined along with the strength voting and weighted ranking method in the hierarchical combination method to obtain an EER of 3.75%.
Бесплатно
Silence Removal and Endpoint Detection of Speech Signal for Text Independent Speaker Identification
Статья научная
In this paper we propose a composite silence removal technique comprising of short time energy and statistical method. The performance of the proposed algorithm is compared with the Short Time Energy (STE) algorithm and the statistical method with varying Signal to Noise Ratio (SNR). In the presence of low SNR the performance of proposed algorithm is highly appreciable in compare to STE and statistical method. We have applied the proposed algorithm in the pre processing stage of speaker identification system. A comparison between the speaker identification rate including and excluding the silence removal technique shows around 20% increase in identification rate by the application of this proposed algorithm.
Бесплатно
Simplified Model for Fire Resistance Analysis on Steel Staggered-truss System under Lateral Force
Статья научная
In order to investigate the simplified method for the fire resistance analysis on the steel staggered-truss system (SSTS) under the lateral force, a three-dimensional (3-D) model, a plane cooperative (PC) model and a planar model are established by the finite element method respectively. The effect of slabs is considered in the models. The mechanical performances of SSTS at elevated temperature were analyzed and the interaction characteristics between the truss exposed to fire and its adjacent trusses are studied. The results obtained by the above different models were comparatively investigated to explore the applicability of different models for the analysis of SSTS under lateral force and high temperature. The results indicate that the adjacent trusses in SSTS under lateral force could keep good coordination at elevated temperature. When applied to the analysis for SSTS under lateral force at elevated temperature, the 3-D model is the best in accord with actual situation while it is complicated and the computation is time-consuming, and the planar model is simple and convenient while it may cause some considerable deviation, and the PC model could simulate the interactions between adjacent frame truss and the truss under fire effectively in the SSTS, whose result is in the propinquity of 3-D model and has an acceptable accuracy. The PC model without rigidly hinged bars (RHB) on the fire floor is recommended to analyze the fire response behaviors of staggered-steel truss system under lateral force.
Бесплатно
Simulation and Experiment of Projectile Penetrate into Steel Target Acceleration Signal Processing
Статья научная
For a comprehensive and objective understanding of the dynamic overload character of projectile penetrate into a steel target, using the simulating software ANSYS/LS-DYNA, adopting of the corresponding ammunition and target model, and the process of the ammunition penetrate the steel target was simulated and computed, the stress distribution map, mode and some results were got, using ball cartridge experiment, the original overload curves and high speed camera results were got. In this paper, the acceleration signals, which are obtained by the embedded high-overload electronic solid recorder at the experiment of armor-piercing bullet penetrating steel target, was done of wave filtering and integral analysis and so on in time domain, power spectrum was got through FFT in frequency-domain, as well as Wigner-Ville analysis and wavelet analysis in timefrequency. The characteristic signal when armor-piercing bullet penetrates steel target under certain conditions was obtained. Through signal processing and comprehensive analysis, a kind of signal processing method was provided to engineers, by which concerned parameters can be got.
Бесплатно
Статья научная
Carbon Nanotube Field Effect Transistors (CNTFETs) are being proposed as candidates for next-generation integrated circuit technology replacing conventional MOSFET devices. It is a suitable nanoelectronic device which is used for high speed and low power design applications which include analog and digital circuits. In this paper, a single wall carbon nanotube field effect transistor (SW-CNTFET) with a coaxial structure in the ballistic regime has been studied and its performance parameters discussed. Numerical simulations were performed based on Natori approach. The various device metrics in consideration are drive current (Ion), Ion/Ioff ratio, output conductance (gd), trans-conductance (gm), gain, carrier injection velocity, sub-threshold swing and drain induced barrier lowering (DIBL). In particular, the influences of gate oxide thickness on the short-channel effects are presented in detail. Also, the dependence of sub-threshold swing and DIBL on the gate control parameter has been discussed.
Бесплатно
Simultaneous Image Fusion and Denoising based on Multi-Scale Transform and Sparse Representation
Статья научная
Multi-scale transform (MST) and sparse representation (SR) techniques are used in an image representation model. Image fusion is used especially in medical, military and remote sensing areas for high resolution vision. In this paper an image fusion technique based on shearlet transformation and sparse representation is proposed to overcome the natural defects of both MST and SR based methods. The proposed method is also used in different transformations and SR for comparison purposes. This research also investigate denoising techniques with additive white Gaussian noise into source images and perform threshold for de-noised into the proposed method. The image quality assessments for the fused image are used for the performance of proposed method and compared with others.
Бесплатно
Sine Cosine Taylor Like Technique for Connected Component Detector by ICNN Simulation
Статья научная
Sine cosine Taylor like technique is employed to carry out connected component detector (CCD) simulation under improved cellular neural network (ICNN) architecture to yield better accuracy for hand written character and image recognition system. The principal simulation results reveal that this technique performs well in comparison with other techniques.
Бесплатно
Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)
Статья научная
In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis) methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis) has less error and system worked more accurate and appropriative than prior methods.
Бесплатно
Статья научная
High utility item-sets mining(HUIM)is a special topic in frequent item-sets mining(FIM). It gives better insights for business growth by focusing on the utility of items in a transaction. HUIM is evolving as a powerful research area due to its vast applications in many fields. Data stream processing, meanwhile, is an interesting and challenging problem since, processing very fast generating a huge amount of data with limited resources strongly demands high-performance algorithms. This paper presents an innovative idea to extract the high utility item-sets (HUIs) from the dynamic data stream by applying sliding window control. Even though certain algorithms exist to solve the same problem, they allow redundant processing or reprocessing of data. To overcome this, the proposed algorithm used a trie like structure called Extended Global Utility Item-sets tree (EGUI-tree), which is flexible to store and retrieve the mined information instead of reprocessing. An experimental study on real-world datasets proved that EGUI-tree algorithm is faster than the state-of-the-art algorithms.
Бесплатно
