Ragesh NK - Academia.edu (original) (raw)

Papers by Ragesh NK

Research paper thumbnail of Pedestrian Detection in Automotive Safety: Understanding State-of-the-Art

Pedestrian detection is one of the important computer vision problems in automotive safety and dr... more Pedestrian detection is one of the important computer vision problems in automotive safety and driver assistance domain. It is a major component of the advanced driver assistance system (ADAS) which help the driver to drive safely. Recent literature shows a number of research activities addressing object detection/tracking in general and pedestrian detection in particular. The solutions proposed by different researchers vary in detection methods, detection scenario, feature descriptors, classification schemes, detection performance, as well as computational complexity. However, the average detection accuracy is not much promising even after many years of research. The fail-safe and real-time human detection from real life road scenes, even in standard resolution, is far from reality. Safety critical systems in the automotive industry have to follow well established stringent safety standards like ISO26262. Since the pedestrian detection system deals with human safety, it also has to follow these standards before integrating to the vehicle electronics. This paper is a study of different techniques used in pedestrian detection specific to the automotive application, along with a description of generic pedestrian detection solution architecture. INDEX TERMS Road safety, advanced driver assistance systems (ADAS), smart image region of interest (ROI) selection, image feature descriptors, pedestrian detection.

Research paper thumbnail of Coherence vector of Oriented Gradients for traffic sign recognition using Neural Networks

… (IJCNN), The 2011 …, Jan 1, 2011

This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognitio... more This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Experiments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The results based on the combination of other features gave better recognition rates.

Research paper thumbnail of Measures for the Quality of Individual Articles, Authors and Journals

International Journal of …, Jan 1, 2010

Journal impact factors are not representatives of the quality measures of individual journal arti... more Journal impact factors are not representatives of the quality measures of individual journal articles, authors and quality factor of journals. Hence, due to the high necessity of quality measures, this paper presents new quality measures for journals, authors and individual journal articles.

Research paper thumbnail of Digital Image Denoising in Medical Ultrasound images: A Survey

ICGST AIML-11 Conference, Dubai, …, Jan 1, 2011

Digital image acquisition and processing techniques plays very important role in current-day medi... more Digital image acquisition and processing techniques plays very important role in current-day medical diagnosis. Images of living objects are taken using different modalities like X-ray, Ultrasound, Computed Tomography (CT), Magnetic Resonance Imaging (MRI) etc. During the acquisition process, there could be distortions in the images, which will negatively affect the diagnosis based on these images. This highlights the importance of applying advanced digital image processing techniques for improving the quality by removing noise components present in the acquired image to have a better diagnosis. Even if there are multiple modalities of medical image acquisition, Ultrasound imaging is mostly used because of its non-invasive nature and lower acquisition cost. However, the presence of noise components is more on Ultrasound image compared to other costlier methods like CT and MRI. In this paper, we present a survey on different techniques used in ultrasound image denoising

Research paper thumbnail of Pedestrian Detection in Automotive Safety: Understanding State-of-the-Art

Pedestrian detection is one of the important computer vision problems in automotive safety and dr... more Pedestrian detection is one of the important computer vision problems in automotive safety and driver assistance domain. It is a major component of the advanced driver assistance system (ADAS) which help the driver to drive safely. Recent literature shows a number of research activities addressing object detection/tracking in general and pedestrian detection in particular. The solutions proposed by different researchers vary in detection methods, detection scenario, feature descriptors, classification schemes, detection performance, as well as computational complexity. However, the average detection accuracy is not much promising even after many years of research. The fail-safe and real-time human detection from real life road scenes, even in standard resolution, is far from reality. Safety critical systems in the automotive industry have to follow well established stringent safety standards like ISO26262. Since the pedestrian detection system deals with human safety, it also has to follow these standards before integrating to the vehicle electronics. This paper is a study of different techniques used in pedestrian detection specific to the automotive application, along with a description of generic pedestrian detection solution architecture. INDEX TERMS Road safety, advanced driver assistance systems (ADAS), smart image region of interest (ROI) selection, image feature descriptors, pedestrian detection.

Research paper thumbnail of Coherence vector of Oriented Gradients for traffic sign recognition using Neural Networks

… (IJCNN), The 2011 …, Jan 1, 2011

This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognitio... more This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Experiments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The results based on the combination of other features gave better recognition rates.

Research paper thumbnail of Measures for the Quality of Individual Articles, Authors and Journals

International Journal of …, Jan 1, 2010

Journal impact factors are not representatives of the quality measures of individual journal arti... more Journal impact factors are not representatives of the quality measures of individual journal articles, authors and quality factor of journals. Hence, due to the high necessity of quality measures, this paper presents new quality measures for journals, authors and individual journal articles.

Research paper thumbnail of Digital Image Denoising in Medical Ultrasound images: A Survey

ICGST AIML-11 Conference, Dubai, …, Jan 1, 2011

Digital image acquisition and processing techniques plays very important role in current-day medi... more Digital image acquisition and processing techniques plays very important role in current-day medical diagnosis. Images of living objects are taken using different modalities like X-ray, Ultrasound, Computed Tomography (CT), Magnetic Resonance Imaging (MRI) etc. During the acquisition process, there could be distortions in the images, which will negatively affect the diagnosis based on these images. This highlights the importance of applying advanced digital image processing techniques for improving the quality by removing noise components present in the acquired image to have a better diagnosis. Even if there are multiple modalities of medical image acquisition, Ultrasound imaging is mostly used because of its non-invasive nature and lower acquisition cost. However, the presence of noise components is more on Ultrasound image compared to other costlier methods like CT and MRI. In this paper, we present a survey on different techniques used in ultrasound image denoising