Informatics Publishing Limited

S. Deepa ¹, V. Sadasivam ²

Affiliations
1 Department of Information Technology, National College of Engineering, Tirunelveli, IN
2 PSN College of Engineering, Melathediyoor, Tirunelveli, IN

Abstract

Multispectral images are images with high spatial, spectral and radiometric resolution. Efficient multispectral image compression plays a key role in most of the geographical applications. The three important phases involved in a adaptive technique are transformation, clustering and encoding based on the resultant clusters. The existing methods like SPIHT, STW, WDR, and ASWDR are used as the base for Adaptive encoding techniques. The methods adopted are the recent wavelet compression techniques adopted for high dimensional images. The paper proposes the adaptive encoding technique and different combination of encoding techniques are evaluated and an efficient technique (E –Ad) is identified by comparing the results using the metrics Peak Signal to Noise Ratio as well as Compression Ratio. The proposed compression technique preserves the unique spectral characteristics of the multispectral image. The compressed image, can be efficiently used as preprocessing for many enhancement techniques and for object classification mechanisms. The E-Ad technique overtakes many of the state of art algorithms.

Keywords

ASWDR, E–Ad, SPIHT, STW, WDR.

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G. Madasamy Raja ¹, V. Sadasivam ²

Affiliations
1 Department of Computer Science and Engineering, M.E.T. Engineering College, Nagercoil, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, IN

Abstract

Digital image enhancement techniques are used for improving the quality of the digital image. Contrast enhancement, one of the digital image enhancement techniques, is a process that normalizes the gray level of the input image so that sudden and unexpected changes in the illumination are removed. Image contrast enhancement techniques are used for extracting several hidden image characteristics from the image background. This paper proposes a new methodology for image contrast enhancement that is based on the concept of normalization of the image contrast with the help of morphological filters. Two methods are proposed here for detecting the image background from the images which are captured with poor lighting, one method uses the combination of opening and closing morphological filters and another method uses top-hat by opening morphological filter. Also, the performance of proposed algorithm for image contrast enhancement is demonstrated against a recently proposed method.

Keywords

Image Background Detection, Image Contrast Enhancement, Morphological Filters, Weber Contrast Measure.

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R. Dhaya ¹, V. Sadasivam ², R. Kanthavel ³

Affiliations
1 Department of Information Technology, National Engineering College, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN
3 Department of Computer Science and Engineering, Government College of Engineering, Tamil Nadu, IN

Abstract

Bluetooth is a low power and cost-effective short range wireless network technology working in 2.4GHz ISM band. Bluetooth can be implemented either in piconet or Scatternet. In piconet the devices can communicate with each other forming a network with maximum of 8 nodes (1 master and 7 slaves). Two or more piconets can be connected through a common Bluetooth device (a gateway or bridge) to form a Scatternet. But the difficult thing is to achieve Quality of service (QoS) in Bluetooth particularly in the Scatternet. Quality of service refers to the efficient management of system resources, which includes the parameters like bandwidth, delay, jitter etc. This paper addresses guaranteed QoS in a Bluetooth scatternet by considering mainly two constraints namely Packet Loss and Waiting time .The above two constraints are met in a Bluetooth scatternet under high traffic congestion, which increases packet delay and causes channel wastage thereby affecting QoS. In the existing First In First Out (FIFO) scheme the slaves are served by the master in accordance with the arrival of the request offered by respective slaves in the form of 'first come first serve' technique. So a proposal to simulate a new priority based scheduling scheme like DST (Dynamic Scheduling Technique) has been implemented, which overcomes the pitfalls like packet loss, waiting time, and high congestion in the FIFO scheduling scheme. The results shows that the proposed DST scheduling that carries dynamic priorities for the requesting slaves by employing dynamic scheduling technique, which assures and guaranties the QoS parameters.

Keywords

Bluetooth, Sensor Network, Scatternet, Quality of Service, Dynamic Scheduling.

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A. Sindhuja ¹, V. Sadasivam ²

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
2 PSN College of Engineering and Technology, IN

Abstract

Elastography is the emerging imaging modality that analyzes the stiffness of the tissue for detecting and classifying breast tumors. Computer-aided detection speeds up the diagnostic process of breast cancer improving the survival rate. A multi resolution approach using Discrete wavelet transform is employed on real time images, using the low-low (LL), low-high (LH), high-low (HL), and high-high (HH) sub-bands of Daubechies family. Features are extracted, selected and then finally segmented by K-means clustering algorithm. The proposed work can be extended to Classification of the tumors.

Keywords

Daubechies Wavelet, Feature Selection, SFFS, K-Means.

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D. Jemi Florinabel ¹, S. Ebenezer Juliet ¹, V. Sadasivam ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, IN

Abstract

A speedy recovery of damaged digitized photographs based on orientation driven multi structure morphology is proposed. The recovery order plays an important factor for human visualization and hence it is guided by the orientation of edges at the surrounding known regions of the missing domain. The image is edge detected by thresholding the image gradient along the eight possible orientations. These eight edge images are represented as eight edge planes. The edge-plane-sliced information is used twice manifold for reconstructing the regions within the missing part, as well as for guiding the integration that follows. The damaged regions are morphologically eroded using the structuring elements of corresponding orientations dictated by the edge-planes. The resultant filled image is obtained using local isotopic driven integration. The novelty of our approach is to explicitly specify the direction of filling herby ensuring ease in convergence in different orientations and then streamlining the process to guarantee complete and natural look. By implementing region-filling through morphological erosion, several pixels instead of one can be restored at every inpainting step, making the method faster than many traditional texture synthesis inpainting algorithms and successfully recovers images with better Peak Signal to Noise ratios even for massive damages.

Keywords

Image Gradient, Morphological Erosion, Structuring Elements, Texture Synthesis, Inpainting.

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B. N. Prathibha ¹, V. Sadasivam ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN

Abstract

Mammography is a well established imaging technique for showing tissue abnormalities of breast and has been proven to reduce death rate due to breast cancer in screened populations of women. The proposed method classifies the breast tissues according to severity of abnormality (benign or malign) using combined transforms domain features. In this paper two such domains are explored, Discrete Cosine Transform - Discrete Wavelet Transform (DCT-DWT) and Discrete Cosine Transform - Stationary Wavelet Transform (DCT-SWT). The method is tested on 221 mammogram images from the MIAS database. The combined transform domain features proves to be a promising tool for precise classification with SVM classifier. The DCT-DWT domain yields 96.26% accuracy for discrimination between normal-malign samples comparing to DCT-SWT which gives 93.14%. The novelty of the proposed method is demonstrated by comparing with nearest neighbor classification technique.

Keywords

Combined Transforms, Mammograms, SVM, Nearest Neighbor Classifier.

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S. Ebenezer Juliet ¹, V. Sadasivam ¹, D. Jemi Florinabel ¹

Affiliations
1 Department of Computer Science and Engineering, Manomaniam Sundaranar University, Tamil Nadu, IN

Abstract

This paper presents a one pass block classification algorithm for efficient coding of compound images which consists of multimedia elements like text, graphics and natural images. The objective is to minimize the loss of visual quality of text during compression by separating text information which needs high special resolution than the pictures and background. It segments computer screen images into text/graphics and picture/background classes based on DCT energy in each 4x4 block, and then compresses both text/graphics pixels and picture/background blocks by H.264/AVC with variable quantization parameter. Experimental results show that the single H.264/AVC-INTRA coder with variable quantization outperforms single coders such as JPEG, JPEG-2000 for compound images. Also the proposed method improves the PSNR value significantly than standard JPEG, JPEG-2000 and while keeping competitive compression ratios.

Keywords

Compound Image Compression, Block Classification, DCT Coefficients, H.264/AVC-Intra

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B. N. Prathibha ¹, V. Sadasivam ¹

Affiliations
1 Department of Computer Science and Engineering, Manomaniam Sundaranar University, Tamil Nadu, IN

Abstract

Breast cancer is a primary cause of mortality and morbidity in women. Reports reveal that earlier the detection of abnormalities, better the improvement in survival. Digital mammograms are one of the most effective means for detecting possible breast anomalies at early stages. Digital mammograms supported with Computer Aided Diagnostic (CAD) systems help the radiologists in taking reliable decisions. The proposed CAD system extracts wavelet features and spectral features for the better classification of mammograms. The Support Vector Machines classifier is used to analyze 206 mammogram images from Mias database pertaining to the severity of abnormality, i.e., benign and malign. The proposed system gives 93.14% accuracy for discrimination between normal-malign and 87.25% accuracy for normal-benign samples and 89.22% accuracy for benign-malign samples. The study reveals that features extracted in hybrid transform domain with SVM classifier proves to be a promising tool for analysis of mammograms.

Keywords

Mammograms, Classification, Hybrid Transforms, SVM.

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P. Arockia Jansi Rani ¹, V. Sadasivam ²

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu,, IN

Abstract

Image compression is very important in reducing the costs of data storage and transmission in relatively slow channels. In this paper, a still image compression scheme driven by Self-Organizing Map with polynomial regression modeling and entropy coding, employed within the wavelet framework is presented. The image compressibility and interpretability are improved by incorporating noise reduction into the compression scheme. The implementation begins with the classical wavelet decomposition, quantization followed by Huffman encoder. The codebook for the quantization process is designed using an unsupervised learning algorithm and further modified using polynomial regression to control the amount of noise reduction. Simulation results show that the proposed method reduces bit rate significantly and provides better perceptual quality than earlier methods.

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G. Muthu Lakshmi ¹, V. Sadasivam ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN

Abstract

In this paper, a new method of vector quantizer design for image compression using Generic codebook and wavelet transformation is proposed. In the proposed method, Self Organizing Feature Map (SOFM) is used for initial codebook generation. A new scheme of wavelet transformation based Vector Quantization (VQ) technique is proposed to replace the SOFM code vectors by VQ code vectors. The proposed wavelet transform is used to generate wavelet coefficients which are then converted into VQ code vectors. Discrete Cosine Transformation based vector quantization technique is proposed in the existing image compression algorithms with low quality images with greater amount of information loss. Hence to increase the psycho visual quality of the reconstructed image wavelet transformation based vector quantization technique is proposed in this paper. Performance of the proposed work is tested with varying codebook size and various training images. Experimental results show that the reconstructed images obtained by the proposed method are of good quality with better compression ratio and higher Peak Signal–to–Noise Ratio.

Keywords

Vector Quantization, Self-Organizing Feature Map, Image Compression, Wavelet Transformations.

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R. Dhaya ¹, V. Sadasivam ², R. Kanthavel ³

Affiliations
1 Dept. of Information Technology, National Engineering College, Kovilpatti, Tamilnadu, IN
2 Dept. of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, IN
3 Dept. of Computer Science and Engineering, Govt. College of Engg., Tirunelveli, Tamilnadu, IN

Abstract

In the recent development of communication, Bluetooth Scatternet wireless is a technology developed for wideband local accesses. Bluetooth technology is very popular because of its low cost and easy deployment which is based on IEEE 802.11 standards. On the other hand Wireless Sensor Network (WSN) consists of large number of sensor nodes distributed to monitor an environment and each node in a WSN consists of a small CPU, a sensing device and battery. Mostly, the sensor networks are distributed in an inconvenient location and it is difficult to recharge often. So routing in WSN is an important issue to consume energy and as well as to increase the life of the network, since a routing protocol finds the path between sources and sink. Moreover it is a challenging task to schedule the data between nodes in a scatternet in a congestive environment. Here this paper presents a new scheduling method for point to multi- point routing in Scatternet sensor network and the new dynamic routing method designed is cluster-based with hierarchical routing. The efficiency of this method is also compared in terms of energy consumption and the results show that the proposed routing is an energy efficient one which simultaneously increases the lifetime of the network.

Keywords

Bluetooth, Dynamic Routing, Hierarchical Routing, Scatternet, Wireless Sensor Networks.

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V. Kavidha ¹, V. Sadasivam ²

Affiliations
1 Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundarnar University, Abishekapatti, Tirunelveli, Tamilnadu, IN

Abstract

High performance data transfer services is needed in long distance high-speed networks. In this paper Adaptive Layered Transmission Control Protocol (ALTCP) is proposed, which is used for making more scalability in high-speed networks. ALTCP is a simple adaptive layering technique for making the Additive Increase Multiplicative Decrease (AIMD) algorithms used by TCP more efficient in probing for the available link bandwidth. ALTCP uses a three-dimensional congestion control framework. First the macroscopic control is employed to layer quickly and made efficient by using available link bandwidth, second microscopic control is used for extends the existing AIMD algorithm of TCP to determine the per acknowledgement behavior. Third the intermediate control is employed for decoupling the aggregate throughout from the number of opened TCP flows in parallel. In this research paper ALTCP protocol is designed and analyzed based on ns-2 simulations. The results show that ALTCP has faster magnitude than TCP in utilizing high bandwidth links. ALTCP has better TCP friendliness and Round Trip Time (RTT) fairness compared with high-speed protocols namely High-speed TCP and Scalable TCP.

Keywords

AIMD, ALTCP, Congestion Control, High Speed Networks, RTT Fairness.

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