Informatics Publishing Limited

K. Somasundaram ¹, S. Vimala ²

Affiliations
1 Department of Computer Science and Applications, Gandhigram Rural Institute, Gandhigram-624302, Tamilnadu, IN
2 Department of Computer Science, Mother Teresa Women’s University, Kodaikanal-624102, Tamilnadu, IN

Abstract

Vector Quantization is a lossy image compression technique. In this paper, we propose a novel idea for generating a codebook by sorting the sum of sub vectors. The training vectors are sub divided into four sub vectors each consisting of four elements.The sum of sub vectors 2 and 4 are subtracted from the sum of sub vectors 1 and 2. The resultant values are used to sort the training vectors. From the sorted list, the training vectors at every nth position are selected to form the codebook. The experimental results and the comparisons show that this method gives better performance with respect to the time taken to generate the codebook and the PSNR value (quality of the reconstructed images). The computational complexity involved is also very less. The codebook generated using the proposed method is optimized using the iterative clustering method. The quality of the reconstructed image is improved to a significant value.

Keywords

Image Compression, Sub Vector, Training Vector, Code Vector and Codebook.

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K. Somasundaram ¹, S. Vimala ²

Affiliations
1 Department of Computer Science and Applications, Gadhigram Rural Institute, Gandhigram – 624302, Tamil Nadu, IN
2 Department of Computer Science, Mother Teresa Women’s University, Kodaikanal – 624 102, Tamil Nadu, IN

Abstract

In this paper, we propose a new technique to retain the edges of the images while compressing them. The image is divided into small blocks of size 4 x 4 pixels. From the list of N image blocks, M (M < N and M is the desired size of codebook) representative blocks are selected to form the codebook. In ordinary codebook generation, all the image blocks are treated equally. But, in the proposed method, the image blocks are classified into high detail blocks and low detail blocks. The high detail blocks represent the edges and the low detail blocks represent the shaded blocks. The high detail blocks are given preference while generating the codebook. Categorization of image blocks improves the quality of the reconstructed images. Codebooks of sizes (M) 128 and 256 are created with the images of size 256 x 256 pixels. The proposed method gives better performance when compared with the results of few existing techniques.

Keywords

Vector Quantization, Training Vector, Code Vector, Codebook, Compression, Edge Block, Shade Block.

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K. O. Sangeethaa ¹, M. Saranya ¹, S. Sornalekha ², S. Vimala ²

Affiliations
1 Department of Electronics and Communication Engineering, Prathyusha Institute of Technology and Management, Thiruvallur, Chennai, IN
2 Department of Electronics and Communication Engineering, Prathyusha Institute of Technology and Management, Thiruvallur, Chennai, IN

Abstract

This paper proposes a simple Wireless Sensor Network (WSN)-based air quality monitoring and fining system for industrial and urban areas. The proposed framework comprises a set of sensors which senses gas (CO), pressure, humidity and temperature that are deployed on stacks and infrastructure of a ZIGBEE WSN and a central server to support both short-term real-time incident management and a long-term strategic planning. The parameters are continuously sensed from the sensor and the penalty will be issued based on their level above threshold value. This architecture would use open-hardware open-software gas sensing capable motes made by Libelium. These motes use the ZIGBEE communication protocol and provide a real-time low cost monitoring system through the use of low cost, low data rate, and low power wireless communication technology. The proposed monitoring system can be transferred to or shared by other applications. We also introduce a simple but efficient clustering protocol dubbed hereafter "Clustering Protocol for Air Sensor network" for the proposed WSN-AQMS framework. CPAS proves to be efficient in terms of network energy consumption, network lifetime, and the rate at which data is communicated.

Keywords

Wireless Sensor Network, Air Quality Monitoring Systems (AQMFS), CO.

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S. Vimala ¹

Affiliations
1 Department of Computer Science, Mother Teresa Women's University, IN

Abstract

Absolute Moment Block Truncation Coding (AMBTC) is one of the lossy image compression techniques. The computational complexity involved is less and the quality of the reconstructed images is appreciable. The normal AMBTC method requires 2 bits per pixel (bpp). In this paper, two novel ideas have been incorporated as part of AMBTC method to improve the coding efficiency. Generally, the quality degrades with the reduction in the bit-rate. But in the proposed method, the quality of the reconstructed image increases with the decrease in the bit-rate. The proposed method has been tested with standard images like Lena, Barbara, Bridge, Boats and Cameraman. The results obtained are better than that of the existing AMBTC method in terms of bit-rate and the quality of the reconstructed images.

Keywords

Compression, Bit-Rate, bpp, Block, Bit-Plane, High-Mean, Low- Mean.

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S. Vimala ¹

Affiliations
1 Department of Computer Science, Mother Teresa Women’s University, IN

Abstract

Vector Quantization (VQ) is one of the Lossy Image Compression Techniques. Vector Quantization comprises of three different phases: Codebook Generation, Image Encoding and Image Decoding. The efficiency of VQ depends on the quality of the codebook. In this paper, we have proposed a novel idea for improving the quality of codebook. The codebook is populated with high detail blocks, with which the edges of the objects in an image can be preserved. The high detail blocks are identified based on the maximum and minimum pixel values of the blocks. K-Means clustering method is also used to improve the quality of the codebook. The quality (PSNR) of the reconstructed images by the proposed method is better when compared to that of few existing codebook generation techniques. Standard images are used to test the performance of the proposed method.

Keywords

Image Compression, Codebook, Training Set, High Detail Block, PSNR.

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S. Vimala ¹, K. Thiagarajan ², A. Amaravathy ¹

Affiliations
1 Department of Mathematics, Mother Teresa Women’s University, Kodaikanal - 624101, Tamil Nadu, IN
2 Department of Mathematics, PSNA College of Engineering and Technology, Dindigul - 624622, Tamil Nadu, IN

Abstract

In this paper a different approach OFSTF (Origin, First, Second, Third, and Fourth quadrants) Method is applied for finding a feasible solution for transportation problems directly. The proposed method is a unique, it gives always feasible (may be optimal for some extant) solution without disturbance of degeneracy condition. This method takes least iterations to reach optimality. A numerical example is solved to check the validity of the proposed method and degeneracy problem is also discussed.

Keywords

Assignment Problem, Degeneracy, Pay Off Matrix (POM), Quadrants, Transportation Problem.

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R. Malathi ¹, B. Shoba ¹, P. Sindhuja ¹, S. Vimala ²

Affiliations
1 Department of Civil Engineering, Sri Ramakrishna Institute of Technology, Coimbatore-641010, IN
2 Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul-624622, IN

Abstract

The leachate is a highly contaminant water hence it needs to be treated. The main aims of this research were to determine the Chemical oxygen demand (COD) concentration and heavy metals (zinc, chromium, lead, cadmium and nickel) in leachate in landfill area. The pollutants were analyzed using coagulation and flocculation process. The coagulants used were the aluminum sulphate (alum) and ferric chloride. The jar test apparatus were employed for the removal of pollutants. The experiments were carried out by varying the dosage of coagulants. The optimum pH level and the dosage level are also found as 8.5 and 3 g/l for ferric chloride and for alum 10.5 and 1.5 g/l. The alum is found to be efficient in the removal of heavy metals and ferric chloride for COD.

Keywords

Leachate, Coagulation-Flocculation, COD, Heavy Metals, Alum, Ferric Chloride.

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