Video Genre Classification Using Weighted Kernel Logistic Regression

Due to the widening semantic gap of videos, computational tools to classify these videos into different genre are highly needed to narrow it. Classifying videos accurately demands good representation of video data and an efficient and effective model to carry out the classification task. Kernel Logistic Regression (KLR), kernel version of logistic regression (LR), proves its efficiency as a classifier, which can naturally provide probabilities and extend to multiclass classification problems. In this paper, Weighted Kernel Logistic Regression (WKLR) algorithm is implemented for video genre classification to obtain significant accuracy, and it shows accurate and faster good results

Detection of prostate cancer using multi-parametric magnetic resonance

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaves 26-28).A multi-channel statistical classifier to detect prostate cancer was developed by combining information from 3 different MR methodologies: T2-weighted, T2-mapping, and Line Scan Diffusion lmaging(LSDI). From these MR sequences, 4 sets of image intensities were obtained: T2-weighted(T2W) from T2-weighted imaging, Apparent Diffusion Coefficient(ADC) from LSDI, and Proton Density (PD) and T2 (T2Map) from T2-mapping imaging. Manually- segmented tumor labels from a radiologist were validated by biopsy results to serve as tumor "ground truth." Textural features were derived from the images using co-occurrence matrix and discrete cosine transform. Anatomical location of voxels was described by a cylindrical coordinate system. Statistical jack-knife approach was used to evaluate our classifiers. Single-channel maximum likelihood(ML) classifiers were based on 1 of the 4 basic image intensities. Our multi-channel classifiers: support vector machine (SVM) and fisher linear discriminant(FLD), utilized 5 different sets of derived features. Each classifer generated a summary statistical map that indicated tumor likelihood in the peripheral zone(PZ) of the gland. To assess classifier accuracy, the average areas under the receiver operator characteristic (ROC) curves were compared. Our best FLD classifier achieved an average ROC area of 0.839 (±0.064) and our best SVM classifier achieved an average ROC area of 0.761 (±0.043). The T2W intensity maximum likelihood classifier, our best single-channel classifier, only achieved an average ROC area of 0.599 (± 0.146). Compared to the best single-channel ML classifier, our best multi-channel FLD and SVM classifiers have statistically superior ROC performance with P-values of 0.0003 and 0.0017 respectively from pairwise 2-sided t-test. By integrating information from the multiple images and capturing the textural and anatomical features in tumor areas, the statistical summary maps can potentially improve the accuracy of image-guided prostate biopsy and enable the delivery of localized therapy under image guidance.by Ian Chan.M.Eng

Secure digital documents using Steganography and QR Code

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonWith the increasing use of the Internet several problems have arisen regarding the processing of electronic documents. These include content filtering, content retrieval/search. Moreover, document security has taken a centre stage including copyright protection, broadcast monitoring etc. There is an acute need of an effective tool which can find the identity, location and the time when the document was created so that it can be determined whether or not the contents of the document were tampered with after creation. Owing the sensitivity of the large amounts of data which is processed on a daily basis, verifying the authenticity and integrity of a document is more important now than it ever was. Unsurprisingly document authenticity verification has become the centre of attention in the world of research. Consequently, this research is concerned with creating a tool which deals with the above problem. This research proposes the use of a Quick Response Code as a message carrier for Text Key-print. The Text Key-print is a novel method which employs the basic element of the language (i.e. Characters of the alphabet) in order to achieve authenticity of electronic documents through the transformation of its physical structure into a logical structured relationship. The resultant dimensional matrix is then converted into a binary stream and encapsulated with a serial number or URL inside a Quick response Code (QR code) to form a digital fingerprint mark. For hiding a QR code, two image steganography techniques were developed based upon the spatial and the transform domains. In the spatial domain, three methods were proposed and implemented based on the least significant bit insertion technique and the use of pseudorandom number generator to scatter the message into a set of arbitrary pixels. These methods utilise the three colour channels in the images based on the RGB model based in order to embed one, two or three bits per the eight bit channel which results in three different hiding capacities. The second technique is an adaptive approach in transforming domain where a threshold value is calculated under a predefined location for embedding in order to identify the embedding strength of the embedding technique. The quality of the generated stego images was evaluated using both objective (PSNR) and Subjective (DSCQS) methods to ensure the reliability of our proposed methods. The experimental results revealed that PSNR is not a strong indicator of the perceived stego image quality, but not a bad interpreter also of the actual quality of stego images. Since the visual difference between the cover and the stego image must be absolutely imperceptible to the human visual system, it was logically convenient to ask human observers with different qualifications and experience in the field of image processing to evaluate the perceived quality of the cover and the stego image. Thus, the subjective responses were analysed using statistical measurements to describe the distribution of the scores given by the assessors. Thus, the proposed scheme presents an alternative approach to protect digital documents rather than the traditional techniques of digital signature and watermarking