Browsing by Author "Madumbu, V."
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Item Design and implementation of an automatic traffic sign recognition system on TI OMAP-L138(2013) Phalguni; Ganapathi, K.; Madumbu, V.; Rajendran, R.; Sumam, David S.This paper discusses the design and processor implementation of a system that detects and recognizes traffic signs present in an image. Morphological operators, segmentation and contour detection are used for isolating the Regions of Interest (ROIs) from the input image, while five methods - Hu moment matching, histogram based matching, Histogram of Gradients based matching, Euclidean distance based matching and template matching are used for recognizing the traffic sign in the ROI. A classification system based on the shape of the sign is adopted. The performance of the various recognition methods is evaluated by comparing the number of clock cycles used to run the algorithm on the Texas Instruments TMS320C6748 processor. The use of multiple methods for recognizing the traffic signs allows for customization based on the performance of the methods for different datasets. The experiments show that the developed system is robust and well-suited for real-time applications and achieved recognition and classification accuracies of upto 90%. � 2013 IEEE.Item Design and implementation of an automatic traffic sign recognition system on TI OMAP-L138(2013) Phalgun; I Ganapathi, K.; Madumbu, V.; Rajendran, R.; Sumam David, S.This paper discusses the design and processor implementation of a system that detects and recognizes traffic signs present in an image. Morphological operators, segmentation and contour detection are used for isolating the Regions of Interest (ROIs) from the input image, while five methods - Hu moment matching, histogram based matching, Histogram of Gradients based matching, Euclidean distance based matching and template matching are used for recognizing the traffic sign in the ROI. A classification system based on the shape of the sign is adopted. The performance of the various recognition methods is evaluated by comparing the number of clock cycles used to run the algorithm on the Texas Instruments TMS320C6748 processor. The use of multiple methods for recognizing the traffic signs allows for customization based on the performance of the methods for different datasets. The experiments show that the developed system is robust and well-suited for real-time applications and achieved recognition and classification accuracies of upto 90%. © 2013 IEEE.Item Robust hand gesture recognition system using motion templates(2011) Kulkarni, S.; Manoj, H.; Sumam, David S.; Madumbu, V.; Kumar, Y.S.This paper presents a robust hand gesture analysis system. The approach uses the video analytic technique of motion templates rather than conventional gesture recognition algorithms. Also, it utilizes background modeling and skin pixel detection which further strengthens the approach by making it tolerant to background clutter and noise. In addition it reduces the false detections to a considerable extent. The system does not necessitate the user to wear any coloured caps or gloves for the hands. Encouraging results were obtained and it was found that the methodology is flexible and can be manipulated to suit gesture based interaction as per the requirements of a system. It can also be implemented as a standalone system. � 2011 IEEE.Item Robust hand gesture recognition system using motion templates(2011) Kulkarni, S.; Manoj, H.; Sumam David, S.; Madumbu, V.; Kumar, Y.S.This paper presents a robust hand gesture analysis system. The approach uses the video analytic technique of motion templates rather than conventional gesture recognition algorithms. Also, it utilizes background modeling and skin pixel detection which further strengthens the approach by making it tolerant to background clutter and noise. In addition it reduces the false detections to a considerable extent. The system does not necessitate the user to wear any coloured caps or gloves for the hands. Encouraging results were obtained and it was found that the methodology is flexible and can be manipulated to suit gesture based interaction as per the requirements of a system. It can also be implemented as a standalone system. © 2011 IEEE.