Detection of broken manhole cover using improved Hough and image contrast

The damage or loss of urban road manhole covers may cause great risk to residents＇ lives and property if they cannot be discovered in time. Most existing research recommendations for solving this problem are difficult to implement. This paper proposes an algorithm that combines the improved Hough transform and image comparison to identify the damage or loss of the manhole covers in complicated surface conditions by using existing urban road video images. Focusing on the pre-processed images, the edge contour tracking algorithm is applied to find all of the edges. Then with the improved Hough transformation, color recognition and image matching algorithm, the manhole cover area is found and the change rates of the manhole cover area are calculated. Based on the threshold of the change rates, it can be determined whether there is potential damage or loss in the manhole cover. Compared with the traditional Hough transform, the proposed method can effectively improve the processing speed and reduce invalid sampling and accumulation. Experimental results indicate that the proposed algorithm has the functions of effective positioning and early warning in the conditions of complex background, different perspectives, and different videoing time and conditions, such as when the target is partially covered.

Fast speedometer identification in dynamic scene based on phase correlation

Speedometer identification has been researched for many years.The common approaches to that problem are usually based on image subtraction,which does not adapt to image offsets caused by camera vibration.To cope with the rapidity,robust and accurate requirements of this kind of work in dynamic scene,a fast speedometer identification algorithm is proposed,it utilizes phase correlation method based on regional entire template translation to estimate the offset between images.In order to effectively reduce unnecessary computation and false detection rate,an improved linear Hough transform method with two optimization strategies is presented for pointer line detection.Based on VC＋＋ 6.0 software platform with OpenCV library,the algorithm performance under experiments has shown that it celerity and precision.

Abnormal driving behavior identification based on direction and position offsets

Abnormal driving behavior identification( ADBI) has become a research hotspot because of its significance in driver assistance systems. However,current methods still have some limitations in terms of accuracy and reliability under severe traffic scenes. This paper proposes a new ADBI method based on direction and position offsets,where a two-factor identification strategy is proposed to improve the accuracy and reliability of ADBI. Self-adaptive edge detection based on Sobel operator is used to extract edge information of lanes. In order to enhance the efficiency and reliability of lane detection,an improved lane detection algorithm is proposed,where a Hough transform based on local search scope is employed to quickly detect the lane,and a validation scheme based on priori information is proposed to further verify the detected lane. Experimental results under various complex road conditions demonstrate the validity of the proposed ADBI.

Intelligent Breakage Assessment of Composite Insulators on Overhead Transmission Lines by Ellipse Detection Based on IRHT

With the development of unmanned aerial vehicle(UAV)technology,visible images are playing an important role in the maintenance of power systems.To achieve the shed breakage evaluation of composite insulators by UAV visible images,an intelligent fault assessment method is proposed.First,the composite insulators in visible light images are identified by Faster-RCNN.After image preprocessing,the image is enhanced and the noise is removed.Then,a canny operator is used to extract the edge of the sheds.An Improved Randomized Hough Transform(IRHT)is used to detect the ellipses in the edge image.The parameters of the detected ellipse,length of major axes and minor axes,center coordinates and deflection angle of major axes,are used to realize the segmentation of the composite insulator.Finally,the number of pixel points in the ellipse and the distance between the points and the ellipse boundary are used to judge whether there are breakage or cracks on the sheds.The area ratio of the breakage to the whole shed is calculated based on the number of pixel points inside the broken area.This method can be realized without a large amount of training dataset of the specific fault type and provides a technical basis for the online fault assessment of a composite insulator on overhead transmission lines.