Traffic Sign Detection and Classification based on Combination of MSER Features and Multi-language OCR

Road signs are so important because they help preserve safe driving conditions; they also influence the safety of drivers and pedestrians. Without these signs, no one would know the driving speed limit, on which direction to drive down a road, any upcoming hazard, or whether they are approaching a merge. It would be chaotic to drive in such situations. Moreover, these signs help new drivers to find their way in the absence of navigators. Therefore, traffic sign recognition takes a critical place in computer vision applications to develop an effective algorithm. In order to tackle this challenge, we proposed the use of Multi-language Traffic Sign Detection and Classification. One of our contributions in this work is that, instead of using the standard grayscale image, we used the RGB colored image. This image is converted into the 2D highest-level grayscale image using the largest values of each pixel in the RGB channels. The novel generated image has the strongest features of the RGB image that make the features distinct and more informative in the classification step. Consider that, in general, the traffic sign has two colors only, the foreground (text location) and background (non-text location). The Maximally Stable Extremal Regions (MSER) used to extract features from the 2D image where the locations of interest are well-identified exclusively by an extremal property of the intensity function in the location and on its outer boundary. The geometrical properties and thinning operations were used to remove the non-text locations. A multi-language OCR was used to understand multi-language. This proposed method has been tested using 240 images which were collected from the Internet and two datasets. The experimental results demonstrated the performance of the proposed method where the traffic sign detected in 92% of the tested images with a very high percentage of localization.

An improved fast segmentation algorithm for text and graphics data

The application of video and image segmentation is carried out from the aspects of improving the accuracy of segmentation and reducing the calculation time, but the segmentation result is affected by the initial curve position, so this paper proposes a new method. As an important part of the Internet, pictures are usually used to help visitors understand. The image contains a lot of deep-level video information, which is an important basis for video content retrieval and data analysis. In this paper, combining the texture and edge features of the image in the process of text location, a multi-scale Gabor filter bank is proposed to transform the original image, and a priori knowledge of the text region is used to process the non-text object in the transform result. In the part of extracting text from pictures, and improved TF-IDF algorithm, BC-TF-IDF algorithm, is proposed to extract text from pictures. To ensure the integrity of the extracted image, the Sobel algorithm is used to process the image in the edge extraction step. Finally, the above method is applied to the Weibo network, and a system of collecting and recognizing the character content of the Weibo image is set up, which completes the function of collecting and gradually recognizing the Weibo image, and verifies the proposed localization method.

Investigation of Switching Sequences on a Generalized SVPWM Algorithm for Multilevel Inverters

This paper investigates the various switching sequences on a generalized 60[Formula: see text] distributed coordinate system-based space vector pulse width modulation (SVPWM) algorithm for multilevel inverters. The main focus of this work is to improve the inverter output voltage profile by taking advantage of the redundancy inverter switching states. With the help of SVPWM algorithm, the three nearest vectors have to find out the synthesis of the [Formula: see text] location and then by applying the various optimum switching sequences, the inverter produces less harmonic content in the output voltage compared to the conventional switching sequence. All the switching sequence designs are developed with the help of minimum change detector (MCD) by using switching redundancies in order to reduce inverter switching loss. Simulation results to analyze various sequences on the general SVPWM algorithm are presented in the seven-level cascaded H-bridge (CHB) inverter. To validate the results, hardware results are presented on the seven-level CHB inverter.

THE TYPHOON DISASTER ANALYSIS BASED ON WEIBO TOPIC HEAT

Could social media data be utilized in hazard evaluation? Typhoon disaster as one of the costly disaster has become devastating threats for human. Moreover, social media change the communication way of human and citizens can turn to this platform to express disasterrelated information at real time. Therefore, social media improves situational awareness and widens the method of hazard information acquiring. With more and more studies investigating in relationship between social media response and degree of damage, the strong correlation has been proved. Weibo as one of the most popular social media in China can provide data with posted text, location, user identification and other additional information. Combining with 10 tropical cyclones and Weibo data in 2013, We perform a quantitative analysis between the grade of hazard situation and Weibo related topic heat in province scale. We provide a new model of Weibo topic heat to evaluate the Weibo activity in study area. Also we demonstrate the hazard assessing formula is H = 1.8845 ln(α) + 15.636 in tropical cyclone disaster. High level goodness of curve fitting also suggest that this equation can be used for rapid assessment of hazard caused by tropical cyclones.

Needle Tip Position Accuracy Evaluation Experiment for Puncture Robot in Remote Center Control

[abstFig src='/00280006/15.jpg' width='300' text='Location of devices in the experiment' ] In recent years, a medical procedure called interventional radiology (IR) has been attracting considerable attention. Doctors can perform IR percutaneously while observing the fluoroscopic image of patients. Therefore, this surgical method is less invasive. In this surgery, computed tomography (CT) equipment is often used for precise fluoroscopy. However, doctors are exposed to strong radiation from the CT equipment. In order to overcome this problem, we have developed a remote-controlled surgical assistance robot called Zerobot. In animal puncture experiment, the operation of Zerobot was based on joint control. Therefore, during a surgery, the tip of the needle moves when a surgeon orders for a change in the direction of the needle. This makes the robot less user-friendly because the surgeon tracks the trajectory of the tip of the needle. This problem can be solved by using remote center control.