Real-Time Panoramic Image Mosaic via Harris Corner Detection on FPGA

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

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Yawning Detection Based on Mouth Feature Points Curve Fitting

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.605-607.2227 ◽

2012 ◽

Vol 605-607 ◽

pp. 2227-2231

Author(s):

Wu Yang Ding ◽

Ling Zhang ◽

Yun Hua Chen

Keyword(s):

Mathematical Model ◽

Real Time ◽

Curve Fitting ◽

Detection Method ◽

Detection Algorithm ◽

Corner Detection ◽

Feature Points ◽

Harris Corner ◽

Fatigue Monitoring ◽

Harris Corner Detection

A yawning detection method which can be used in drivers’ fatigue monitoring is proposed. To adapt to the variance in different mouth shapes and sizes, it based on mouth inner contour corner detection and curve fitting. First, the Harris corner detection algorithm was used to detect inner mouth feature points. Second, we established the open mouths’ mathematical model by curve fitting those points, calculated the degree of mouth openness using the mouth model, and generated the real-time M-curve. Third, the duration of big openness in successive images is divided into levels for further judgment. The validation results show that the method can obtain more precise mouth parameters and distinguish yawn from complex mouth activities. So the method achieves a higher level of accuracy.

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Substation Remote Viewing Image Mosaic based on Canny Operator and Harris Corner Detection

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science ◽

10.2991/lemcs-15.2015.266 ◽

2015 ◽

Author(s):

Yufan Wang

Keyword(s):

Corner Detection ◽

Image Mosaic ◽

Canny Operator ◽

Harris Corner ◽

Harris Corner Detection ◽

Remote Viewing

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An Improved Harris Corner Detection Algorithm for Noised Images

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.6151 ◽

2012 ◽

Vol 433-440 ◽

pp. 6151-6156 ◽

Cited By ~ 1

Author(s):

Xin Zhang ◽

Xiu Hua Ji

Keyword(s):

Image Registration ◽

Detection Algorithm ◽

Experimental Results ◽

Corner Detection ◽

Detection Accuracy ◽

Image Mosaic ◽

Harris Corner ◽

Noise Impact ◽

Corner Points ◽

Harris Corner Detection

The Harris corner detection algorithm is widely applied in image mosaic, which is simple and stable. However, the algorithm has a disadvantage that it obtains a lot of false corners when there exist some noise in an image. An improved Harris corner detection algorithm is proposed in this paper. The new algorithm reduces the noise impact greatly. The experimental results show that the improved algorithm not only reduces false corner points greatly, but also retain the majority of true corners. As a result, it improves the detection accuracy and reduces the chance of error matching in image registration.

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