Real-time Sign Object Detection in Subway station using Rotation-invariant Zernike Moment

Weon, Sun-Hee; Kim, Gye-Young; Choi, Hyung-Il

doi:10.9728/dcs.2011.12.3.279

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2016

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“…SIFT selects the local maxima and generates a descriptor as feature points by using a histogram of the surrounding area in an image. This method serves to strength the distortion or partial change of the image, but a significant amount of calculation occurs to generate the feature vector of 128 dimensions [15,16]. This paper uses image gradient to extract target contour and Radon transform to extract rotation invariant feature.…”

Section: Introductionmentioning

confidence: 99%

Rotation Invariant Automatic Infrared Target Recognition using G-Radon

Won

Kim

2016

MATEC Web of Conferences

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Abstract. In recent research, automatic target recognition (ATR) of infrared targets has been taking a lot of interest to the researchers. A rotation invariant method is useful in target recognition, classification and image analysis to reduce the number of training data. In particular, rotation invariant method, Radon transform, is an effective technique that is used for medical care such as computerized tomography (CT) image. This paper proposes a new rotation invariant algorithm for target recognition. The proposed method combines the gradient information and radon transform. The propose method, called gradient Radon (G-Radon), is applied to synthesized infrared images and compared with traditional radon transform and Zernike moments for validation.

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Section: Introductionmentioning

confidence: 99%