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Mohamed Sathik, M.
- Multilevel Approach of CBIR Techniques for Vegetable Classification Using Hybrid Image Features
Abstract Views :234 |
PDF Views:5
Authors
Affiliations
1 Department of Computer Science, Nesamony Memorial Christian College, IN
2 Sadakathullah Appa College, IN
1 Department of Computer Science, Nesamony Memorial Christian College, IN
2 Sadakathullah Appa College, IN
Source
ICTACT Journal on Image and Video Processing, Vol 6, No 3 (2016), Pagination: 1174-1179Abstract
CBIR is a technique to retrieve images semantically relevant to query image from an image database. The challenge in CBIR is to develop a method that should increase the retrieval accuracy and reduce the retrieval time. In order to improve the retrieval accuracy and runtime, a multilevel CBIR approach is proposed in this paper. In the first level, the color attributes like mean and standard deviations are proposed to calculate on HSV color space to retrieve the images with minimum disparity distance from the database. In order to minimize search area, in the second level Local Ternary Pattern is proposed on images which were selected from the first level. Experimental results and comparisons demonstrate the superiority of the proposed approach.Keywords
Content Based Image Retrieval (CBIR), Gray Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP), Local Ternary Pattern (LTP).
- Efficiency Analysis and Security Evaluation of Block based Image Encryption Schemes
Abstract Views :193 |
PDF Views:2
Authors
Affiliations
1 MCA Dept., PET Engineering College, Vallioor, IN
2 Sadakathullah Appa College, Tirunelveli, IN
1 MCA Dept., PET Engineering College, Vallioor, IN
2 Sadakathullah Appa College, Tirunelveli, IN
Source
Digital Image Processing, Vol 7, No 1 (2015), Pagination: 29-32Abstract
In open network Encryption is used to transmit data securely. Each type of data has its own features, therefore to protect confidential image data from unauthorized access different techniques should be used. A framework is presented in this paper to evaluate image encryption schemes. A number of parameters such as correlation coefficient, information Entropy and a number of pixel change rate are used to quantify the security of encrypted images instead of visual inspection. Encryption efficiency analysis and security evaluation of some schemes like Zonal Transformation Matrix Method and Primitive Root Based Image Encryption schemes are presented. Experimental results demonstrate that the Zonal Transformation Matrix Method provides effective performance and security compared to primitive ischolar_main based encryption scheme.
Keywords
Encryption, Zonal Transformation Matrix, Primitive Root Theorem.- Performance Evaluation of Block based Image Encryption Algorithms
Abstract Views :204 |
PDF Views:2
Authors
Affiliations
1 MCA Dept., PET Engineering College, Vallioor, IN
2 Sadakathullah Appa College, Tirunelveli, IN
1 MCA Dept., PET Engineering College, Vallioor, IN
2 Sadakathullah Appa College, Tirunelveli, IN
Source
Digital Image Processing, Vol 6, No 8 (2014), Pagination: 342-345Abstract
With the fast development of data exchange in electronic system, safety of information is becoming more important in data storage and transmits. Because of commonly using images in industrial practice, it is very important to protect the confidential data from unauthorized access. This paper suggests that image encryption and decryption process based on block based encryption. The algorithms consider here are zonal based image encryption and primitive ischolar_main based image encryption. The zone based image encryption is working based on the principle of zonal transformation matrix, whereas primitive ischolar_main based image encryption is based on the principle of primitive ischolar_main theorem. The attribute considered for the comparative study are information entropy and average deviation analysis. Experimental results demonstrate that the zone based image encryption method provides effective performance compared to primitive ischolar_main based encryption method.
Keywords
Encryption, Decryption, Transformation Matrix, Primitive Root Theorem.- Development of Hybrid Image by Fusion
Abstract Views :226 |
PDF Views:1
Authors
Affiliations
1 Sadakathullah Appa College, Tirunelveli, IN
2 Manonmaniam Sundaranar University, Tirunelveli, IN
1 Sadakathullah Appa College, Tirunelveli, IN
2 Manonmaniam Sundaranar University, Tirunelveli, IN
Source
Digital Image Processing, Vol 3, No 3 (2011), Pagination: 163-168Abstract
The focus of the image is normally at the center of the photograph. The images with objects with different distance have the problem of lacking focus on some of the objects. In order to overcome this problem, a simple and effective method is proposed. The proposed method may be incorporated in a digital camera to capture images with different focuses of the same image. Then these images can be fused together to get a hybrid image with the details of focused area of all the images of a frame. Initially the RGB color images with different focuses of the same image are captured and converted to gray images. These images are subjected to a filtering operation with an overlapping window of order 3x3. The filtering operation finds the maximum difference of the center pixel with the neighboring eight pixels. A sliding window of order n x n is selected in all the images, the sum of the magnitude values of the difference are computed. The block in the image with higher block sum is selected and is fused with hybrid image. This hybrid image will have more details compared to the ordinary high quality image with single focus. The hybrid image generated helps in inspection to extract more details.Keywords
Camera Automation, Edge Detection, Filtering, Image Fusion.- Hybrid Compression of Color Mosaic Images Using Histogram Based Segmentation
Abstract Views :192 |
PDF Views:3
Authors
Affiliations
1 Department of Computer Science, Sadakathullah Appa College, Tirunelveli, IN
2 Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, IN
1 Department of Computer Science, Sadakathullah Appa College, Tirunelveli, IN
2 Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, IN
Source
Digital Image Processing, Vol 3, No 2 (2011), Pagination: 85-92Abstract
Color Filter Arrays (CFAs) are used in Single sensor cameras to capture the images. The sensors in a CFA are arranged based on Bayer pattern to capture any one of the Red, Green or Blue components of a pixel. The image captured by this type of CFAs is known as mosaic image. The compression ratios achieved while compressing these mosaic images are normally low for all the classical compression methods. Different strategy has to be adopted for compressing mosaic images due to the roughness caused by interleaving of components. This paper proposes a hybrid method by which the mosaic images are compressed by preserving the main subject after segmenting using histogram. The background of the image is stored with some level of loss. Compression ratio is increased by using the proposed hybrid method than the existing methods.Keywords
Image Compression, Mosaic Image, Segmentation.- An Image Encryption Decryption Method Using Secret Based Transformation Matrix
Abstract Views :194 |
PDF Views:2
Authors
Affiliations
1 Sadakathullah Appa College, Tirunelveli, IN
2 S. T. Hindu College, Nagercoil, IN
1 Sadakathullah Appa College, Tirunelveli, IN
2 S. T. Hindu College, Nagercoil, IN
Source
Digital Image Processing, Vol 2, No 10 (2010), Pagination: 401-404Abstract
Due to the unlimited growth of Internet and communication technologies, the extensive use of images in diverse areas such as medical, military, science, engineering, art, entertainment, advertising, education has become unavoidable. With the increasing use of digital techniques for transmitting and storing images, the fundamental issue of protecting the confidentiality, integrity as well as the authenticity of images has become a major concern. This paper proposes a new encryption and decryption algorithm based on transformation matrix. According to this, there are two levels of process. In the first level the block matrix of size 3 x 3 is constructed using the secret key. In the second level, the zone of size 6 x 6 is constructed from the block matrix. The two levels are repeated to get the transformation matrix and is used for encryption purpose. The experimental results are compared with various image encryption algorithms.Keywords
Block, Encryption, Transformation Matrix, Zone.- An Efficient Method of Video Mining to Recognize the Speech of the Video Objects
Abstract Views :268 |
PDF Views:2
Authors
Affiliations
1 M.S. University, Tirunelveli, IN
2 Research and Development Centre, Bharathiyar University, Coimbatore, IN
3 Sadakathullah Appa College, Tirunelveli - 627 001, IN
1 M.S. University, Tirunelveli, IN
2 Research and Development Centre, Bharathiyar University, Coimbatore, IN
3 Sadakathullah Appa College, Tirunelveli - 627 001, IN
Source
Data Mining and Knowledge Engineering, Vol 3, No 1 (2011), Pagination: 18-22Abstract
Mining is the process of extracting particular information from the large amount of data stored in the database or data warehouse. The focusing area in mining process is very vast including the process of Knowledge Mining, Gold Mining and so on. Mining is an important task since there exist many unwanted data along with the needed data. In the stepping stone of data mining, there may the need for mining in the area of Video. The process of extracting the particular object from the video is termed by a misnomer called ―Video Mining‖. Video Mining is one of the emerging technologies in this research world. Due to these properties, in this paper, we presented the concept of Video Mining as the process to extract the particular object from the playing video and analyses its role. Also we can able to retrieve the extracted object’s name and recognize the speech of the object through the technique of Speech Recognizer. Thus this paper produces the valuable technique that will be efficient to carry out the task of Video Mining.Keywords
Data Warehouse, Gold Mining, Knowledge Mining, Misnomer, Speech Recognizer, Stepping Stone, Video Mining.- Hybrid Compression of Cervical Images by Segmenting Nuclei-Cytoplasm
Abstract Views :238 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, Nesamony Memorial Christian College, IN
2 Sadakathullah Appa College, IN
3 Department of Statistics, Manonmaniam Sundaranar University, IN
1 Department of Computer Science, Nesamony Memorial Christian College, IN
2 Sadakathullah Appa College, IN
3 Department of Statistics, Manonmaniam Sundaranar University, IN
Source
ICTACT Journal on Image and Video Processing, Vol 3, No 2 (2012), Pagination: 522-525Abstract
A hybrid image compression method is proposed by which the Nuclei-Cytoplasm of the image is completely restorable and the background part of the image is restorable with insignificant loss. In Hybrid Compression of Cervical Images by Segmenting Nuclei-Cytoplasm, the image is subjected to binary segmentation to detect Background and Nuclei-Cytoplasm. The image is compressed by standard lossy compression method. The difference between the lossy image and the original image is computed as residue. The residue at the Nuclei-Cytoplasm area is compressed by standard lossless compression method by which the Nuclei-Cytoplasm area is completely restorable. This method gives a low bit rate than the lossless compression methods.Keywords
Edge Detection, Segmentation, Image Compression.- A Hybrid Region Growing Algorithm for Medical Image Segmentation
Abstract Views :382 |
PDF Views:177
Authors
Affiliations
1 Department of Computer Science, University of Kerala, Trivandrum, IN
2 Sathakathullah Appa College, Tirunelveli, Tamilnadu, IN
3 Department of IT, National College of Engineering, Tirunelveli, Tamilnadu, IN
1 Department of Computer Science, University of Kerala, Trivandrum, IN
2 Sathakathullah Appa College, Tirunelveli, Tamilnadu, IN
3 Department of IT, National College of Engineering, Tirunelveli, Tamilnadu, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 4, No 3 (2012), Pagination: 61-70Abstract
In this paper, we have made improvements in region growing image segmentation. The First one is seeds select method, we use Harris corner detect theory to auto find growing seeds. Through this method, we can improve the segmentation speed. In this method, we use the Improved Harris corner detect theory for maintaining the distance vector between the seed pixel and maintain minimum distance between the seed pixels. The homogeneity criterion usually depends on image formation properties that are not known to the user. We induced a new uncertainty theory called Cloud Model Computing (CMC) to realize automatic and adaptive segmentation threshold selecting, which considers the uncertainty of image and extracts concepts from characteristics of the region to be segmented like human being. Next to region growing operation, we use canny edge detector to enhance the border of the regions. The method was tested for segmentation on X-rays, CT scan and MR images. We found the method works reliable on homogeneity and region characteristics. Furthermore, the method is simple but robust and it can extract objects and boundary smoothly.Keywords
Region Growing, Segmentation, Seeds Selection, Homogeneity Criterion, Cloud Model.Full Text
- Face Recognition Based on Local Derivative Tetra Pattern
Abstract Views :351 |
PDF Views:5
Authors
Affiliations
1 Department of Computer Applications, Nesamony Memorial Christian College, IN
2 Department of Computer Science, Sadakathullah Appa College, IN
3 Department of Computer Science, Nesamony Memorial Christian College, IN
1 Department of Computer Applications, Nesamony Memorial Christian College, IN
2 Department of Computer Science, Sadakathullah Appa College, IN
3 Department of Computer Science, Nesamony Memorial Christian College, IN
Source
ICTACT Journal on Image and Video Processing, Vol 7, No 3 (2017), Pagination: 1393-1400Abstract
This paper proposes a new face recognition algorithm called local derivative tetra pattern (LDTrP). The new technique LDTrP is used to alleviate the face recognition rate under real-time challenges. Local derivative pattern (LDP) is a directional feature extraction method to encode directional pattern features based on local derivative variations. The nth -order LDP is proposed to encode the first (n-1)th order local derivative direction variations. The LDP templates extract high-order local information by encoding various distinctive spatial relationships contained in a given local region. The local tetra pattern (LTrP) encodes the relationship between the reference pixel and its neighbours by using the first-order derivatives in vertical and horizontal directions. LTrP extracts values which are based on the distribution of edges which are coded using four directions. The LDTrP combines the higher order directional feature from both LDP and LTrP. Experimental results on ORL and JAFFE database show that the performance of LDTrP is consistently better than LBP, LTP and LDP for face identification under various conditions. The performance of the proposed method is measured in terms of recognition rate.Keywords
Local Binary Pattern (LBP), Local Ternary Pattern (LTP), Local Derivative Pattern (LDP), Local Tetra Pattern (LTrP).References
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- W. Zhao, R. Chellappa P.J. Phillips and A. Rosenfeld, “Face Recognition: A Literature Survey”, ACM Computing Surveys, Vol. 35, No. 4, pp. 399-459, 2003.
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- The Database of Faces, Available at, http://www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces
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- Timo Ahonen, Abdenour Hadid and Matti Pietikainen, “Face Description with Local Binary Patterns: Application to Face Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 12, pp. 2037-2041, 2006.
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- JAFFE images, Available at: http://www.kasrl.org/ jaffe_info.html
- Fire Detection Using Support Vector Machine in Wireless Sensor Network and Rescue Using Pervasive Devices
Abstract Views :147 |
PDF Views:0
Authors
Affiliations
1 Department Of Computer Science, Sadakkathullah Appa College, Tirunelveli, IN
2 Manonmaniam Sundaranar University, Tirunelveli, IN
1 Department Of Computer Science, Sadakkathullah Appa College, Tirunelveli, IN
2 Manonmaniam Sundaranar University, Tirunelveli, IN
Source
International Journal of Advanced Networking and Applications, Vol 2, No 2 (2010), Pagination: 636-639Abstract
In the recent days, environment is polluted day by day due to various factors. One of the causes is smokes during the massive fires. Using Wireless Sensor Networks (WSN) fire can be detected earlier and also initiate the rescue operation before it becomes fire. In this paper, we will examine the possibility Support Vector Machine (SVM) for detecting the Fire which has large data sets. It is achieved by using the sketch of classes distribution which is obtained by using Minimum Enclosing Ball (MEB). This approach has many distinctive advantages on dealing with large data sets particularly forest fire data sets. Also, the Support Vector Machine has gained profound interest among the researchers because of its accuracy and the same is extremely important in this Forest Fire context as the cost of misclassification using a classifier is very high. Hence, this approach using multi class Support Vector Machine shows a higher accuracy in detecting the Forest Fire. The experimental result also shows a better accuracy in predicting the Forest Fire. Further, the rescue process will be initiated through the pervasive devices which are placed around the fire sensational area. This process will suppress the fire sensation and protect the field from the fire. We are including an architectural level procedure for implementing the rescue process.Keywords
Multi Classification, Large Dataset, Pervasive Rescue Devices, Support Vector Machine, Wireless Sensor Networks.Full Text