Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

Spatially Adaptive Image Denoising Techniques Using Directionlets

The aim of the thesis was to design and develop spatially adaptive denoising techniques with edge and feature preservation, for images corrupted with additive white Gaussian noise and SAR images affected with speckle noise. Image denoising is a well researched topic. It has found multifaceted applications in our day to day life. Image denoising based on multi resolution analysis using wavelet transform has received considerable attention in recent years. The directionlet based denoising schemes presented in this thesis are effective in preserving the image specific features like edges and contours in denoising. Scope of this research is still open in areas like further optimization in terms of speed and extension of the techniques to other related areas like colour and video image denoising. Such studies would further augment the practical use of these techniques.

Photothermal Investigations on Certain Plasma Polymerized Thin Films and Near IR Overtone Studies of Some Organic Molecules

Photothermal effect refers to heating of a sample due to the absorption of electromagnetic radiation. Photothermal (PT) heat generation which is an example of energy conversion has in general three kinds of applications. 1. PT material probing 2. PT material processing and 3. PT material destruction. The temperatures involved increases from 1-. 3. Of the above three, PT material probing is the most important in making significant contribution to the field of science and technology. Photothermal material characterization relies on high sensitivity detection techniques to monitor the effects caused by PT material heating of a sample. Photothermal method is a powerful high sensitivity non-contact tool used for non-destructive thermal characterization of materials. The high sensitivity of the photothermal methods has led to its application for analysis of low absorbance samples. Laser calorimetry, photothermal radiometry, pyroelectric technique, photoacoustic technique, photothermal beam deflection technique, etc. come under the broad class ofphotothermal techniques. However the choice of a suitable technique depends upon the nature of the sample, purpose of measurement, nature of light source used, etc. The present investigations are done on polymer thin films employing photothermal beam deflection technique, for the successful determination of their thermal diffusivity. Here the sample is excited by a He-Ne laser (A = 6328...\ ) which acts as the pump beam. Due to the refractive index gradient established in the sample surface and in the adjacent coupling medium, another optical beam called probe beam (diode laser, A= 6500A ) when passed through this region experiences a deflection and is detected using a position sensitive detector and its output is fed to a lock-in amplifier from which the amplitude and phase of the deflection can be directly obtained. The amplitude and phase of the signal is suitably analysed for determining the thermal diffusivity.The production of polymer thin film samples has gained considerable attention for the past few years. Plasma polymerization is an inexpensive tool for fabricating organic thin films. It refers to formation of polymeric materials under the influence of plasma, which is generated by some kind of electric discharge. Here plasma of the monomer vapour is generated by employing radio frequency (MHz) techniques. Plasma polymerization technique results in homogeneous, highly adhesive, thermally stable, pinhole free, dielectric, highly branched and cross-linked polymer films. The possible linkage in the formation of the polymers is suggested by comparing the FTIR spectra of the monomer and the polymer.Near IR overtone investigations on some organic molecules using local mode model are also done. Higher vibrational overtones often provide spectral simplification and greater resolution of peaks corresponding to nonequivalent X-H bonds where X is typically C, N or O. Vibrational overtone spectroscopy of molecules containing X-H oscillators is now a well established tool for molecular investigations. Conformational and steric differences between bonds and structural inequivalence ofCH bonds (methyl, aryl, acetylenic, etc.) are resolvable in the higher overtone spectra. The local mode model in which the X-H oscillators are considered to be loosely coupled anharmonic oscillators has been widely used for the interpretation of overtone spectra. If we are exciting a single local oscillator from the vibrational ground state to the vibrational state v, then the transition energy of the local mode overtone is given by .:lE a......v = A v + B v2 • A plot of .:lE / v versus v will yield A, the local mode frequency as the intercept and B, the local mode diagonal anharmonicity as the slope. Here A - B gives the mechanical frequency XI of the oscillator and B = X2 is the anharmonicity of the bond. The local mode parameters XI and X2 vary for non-equivalent X-H bonds and are sensitive to the inter and intra molecular environment of the X-H oscillator.

An Approach Towards The Development Of An Efficient Symmetric Key Encryption Scheme

n the recent years protection of information in digital form is becoming more important. Image and video encryption has applications in various fields including Internet communications, multimedia systems, medical imaging, Tele-medicine and military communications. During storage as well as in transmission, the multimedia information is being exposed to unauthorized entities unless otherwise adequate security measures are built around the information system. There are many kinds of security threats during the transmission of vital classified information through insecure communication channels. Various encryption schemes are available today to deal with information security issues. Data encryption is widely used to protect sensitive data against the security threat in the form of “attack on confidentiality”. Secure transmission of information through insecure communication channels also requires encryption at the sending side and decryption at the receiving side. Encryption of large text message and image takes time before they can be transmitted, causing considerable delay in successive transmission of information in real-time. In order to minimize the latency, efficient encryption algorithms are needed. An encryption procedure with adequate security and high throughput is sought in multimedia encryption applications. Traditional symmetric key block ciphers like Data Encryption Standard (DES), Advanced Encryption Standard (AES) and Escrowed Encryption Standard (EES) are not efficient when the data size is large. With the availability of fast computing tools and communication networks at relatively lower costs today, these encryption standards appear to be not as fast as one would like. High throughput encryption and decryption are becoming increasingly important in the area of high-speed networking. Fast encryption algorithms are needed in these days for high-speed secure communication of multimedia data. It has been shown that public key algorithms are not a substitute for symmetric-key algorithms. Public key algorithms are slow, whereas symmetric key algorithms generally run much faster. Also, public key systems are vulnerable to chosen plaintext attack. In this research work, a fast symmetric key encryption scheme, entitled “Matrix Array Symmetric Key (MASK) encryption” based on matrix and array manipulations has been conceived and developed. Fast conversion has been achieved with the use of matrix table look-up substitution, array based transposition and circular shift operations that are performed in the algorithm. MASK encryption is a new concept in symmetric key cryptography. It employs matrix and array manipulation technique using secret information and data values. It is a block cipher operated on plain text message (or image) blocks of 128 bits using a secret key of size 128 bits producing cipher text message (or cipher image) blocks of the same size. This cipher has two advantages over traditional ciphers. First, the encryption and decryption procedures are much simpler, and consequently, much faster. Second, the key avalanche effect produced in the ciphertext output is better than that of AES.

Studies in oleoresins an investigation into food colour from Indian chilli oleoresin

This thesis is essentially concerned with a study of the recovery of pungency-free colour matter from capsicum spice of Indian origin. A spice oleoresin may be defined as the total soluble extract of the spice in a specific solvent and embraces all the active components that contribute to aroma, taste and related sensory factors associated with the spice, together with varying amounts of pigments, plant waxes, resins and fixed oils. Whereas, in general, oleoresins are coveted for their flavour qualities, in some cases, the pigments present therein play a vital role in food technology Of these, capsicum oleoresin is the most outstanding, since it contributes both colour and flavour principles.

Content Based Image Retrieval System for Malayalam Handwritten Characters

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

Design, Development and Realization of Quadratic Volterra Filters for Selected Applications

The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals