Soodamani Ramalingam

Bio: Soodamani Ramalingam is an academic researcher from University of Hertfordshire. The author has contributed to research in topics: Edge detection & Multiple-criteria decision analysis. The author has an hindex of 9, co-authored 38 publications receiving 287 citations. Previous affiliations of Soodamani Ramalingam include Manchester Metropolitan University & Middlesex University.

Advances in Fingerprint Technology

Abstract: Fingerprint technology has evolved immensely since its initial use in the 1800s when it was used solely to assist with crime investigations. It is now used as a convenience replacing passwords and PIN numbers from logging into bank accounts, mobile devices, gaining access into rooms and various other processes where time plays a key factor. This chapter focuses on how fingerprint technology can be used to improve speed and accuracy of certain processes, i.e. exams as the society accepts this as part of everyday life. In particular, we look at a use case in an educational setting where youngsters are much used to digital technologies as part of their daily life.

Accuracy of automatic number plate recognition (ANPR) and real world UK number plate problems

Abstract: This paper considers real world UK number plates and relates these to ANPR. It considers aspects of the relevant legislation and standards when applying them to real world number plates. The varied manufacturing techniques and varied specifications of component parts are also noted. The varied fixing methodologies and fixing locations are discussed as well as the impact on image capture.

License plate localisation based on morphological operations

Abstract: Automatic Number Plate Recognition (ANPR) systems allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. This paper presents an improved method to locate car plates in an ANPR system. The proposed method is based on morphological open and close operations where different Structuring Elements (SE) are used to maximally eliminate non-plate region and enhance plate region. This method has been tested using a database of UK number plates and results achieved have shown significant improvements in terms of the detection rate compare to other existing plate localisation systems.

Edge detection comparison for license plate detection

Abstract: The detection of license plate region is the most important part of a vehicle's license plate recognition process followed by plate segmentation and optical character recognition. Edge detection is commonly used in license plate detection as a preprocessing technique. This paper compares the performance of the image enhancement filters when used in edge detection algorithms combined with connected component analysis to extract license plate region. The experimental comparison of Canny, Kirsch, Rothwell, Sobel, Laplace and SUSAN edge detectors on gray scale images shows that Canny yields high plate detection of 98.2% tested on 45,032 UK images containing license plates at 720×288 resolution captured under various illumination conditions. The average processing time of one image is 56.4 ms.

Metadata extraction and classification of YouTube videos using sentiment analysis

Abstract: MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the web.

Fluorescent Nanomaterials for the Development of Latent Fingerprints in Forensic Sciences

Abstract: This review presents an overview on the application of latent fingerprint development techniques in forensic sciences. At present, traditional developing methods such as powder dusting, cyanoacrylate fuming, chemical method, and small particle reagent method, have all been gradually compromised given their emerging drawbacks such as low contrast, sensitivity, and selectivity, as well as high toxicity. Recently, much attention has been paid to the use of fluorescent nanomaterials including quantum dots (QDs) and rare earth upconversion fluorescent nanomaterials (UCNMs) due to their unique optical and chemical properties. Thus, this review lays emphasis on latent fingerprint development based on QDs and UCNMs. Compared to latent fingerprint development by traditional methods, the new methods using fluorescent nanomaterials can achieve high contrast, sensitivity, and selectivity while showing reduced toxicity. Overall, this review provides a systematic overview on such methods.

Impact of digital fingerprint image quality on the fingerprint recognition accuracy

Abstract: Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.

The British Standards Institution

Abstract: The British Standards Institution (BSI) is the body responsible for preparing British Standards. It provides the gateway for UK representation in European and International Standards Organizations. It is a nonprofit organization formed by subscribing members and committee members and incorporated by Royal Charter since 1929. Here, the author covers the work of BSI Committees which are concerned with electricity metering standards with particular emphasis on European standards.< >

Image segmentation: A survey of graph-cut methods

Abstract: As a preprocessing step, image segmentation, which can do partition of an image into different regions, plays an important role in computer vision, objects recognition, tracking and image analysis. Till today, there are a large number of methods present that can extract the required foreground from the background. However, most of these methods are solely based on boundary or regional information which has limited the segmentation result to a large extent. Since the graph cut based segmentation method was proposed, it has obtained a lot of attention because this method utilizes both boundary and regional information. Furthermore, graph cut based method is efficient and accepted world-wide since it can achieve globally optimal result for the energy function. It is not only promising to specific image with known information but also effective to the natural image without any pre-known information. For the segmentation of N-dimensional image, graph cut based methods are also applicable. Due to the advantages of graph cut, various methods have been proposed. In this paper, the main aim is to help researcher to easily understand the graph cut based segmentation approach. We also classify this method into three categories. They are speed up-based graph cut, interactive-based graph cut and shape prior-based graph cut. This paper will be helpful to those who want to apply graph cut method into their research.