Papers by Keyword: Hough Transform (HT)

Abstract: In order to solve the difficulty of low contrast feature extracting between labeled features and background, a new method combined the Hough transform and Canny algorithm is put forward for tensile test using the video extensometer, and a new algorithm edge detection is also obtained based on Canny an feature region tracking as well. The algorithm has proved to be a high positioning accuracy and computational efficiency in the test.

Abstract: Presented paper describes vision-based algorithm for 2D Rubik’s cube state detection suitable for cases in which long-term fixed camera-cube position is not possible. The main focus was to provide a robust algorithm for position and color detection in order to overcome problems observed in previous version. First part of paper describes Hough transform and advanced clustering functions that were used for cube position detection. Described algorithm provides robustness to strong occlusions and various lighting conditions. Second part of paper describes color detection algorithm and problems of prior classification in various color spaces.

Abstract: Linear target is the most widely used in remote sensing image. Effective extraction of the linear target can make us reduce a lot of practical work, thus greatly improve the target extraction and identification of timeliness. According to this situation, in the process of building a recognition system, the recognition efficiency can be realized by joining human recognize and identify, combining with the intelligence of computer processing and powerful place. So in this paper, the method based on edge detection and Hough transform algorithm is exploded. Line Extraction and Target Recognition System is developed. The system is realized under Windows operating system. The tool is Visual C++ 6.0 software. The platform is MFC functions. The system is written in C++ language. The characteristics of the system are the strong pertinence and the simple operation. When the system is applied safely, the results are definite and clear.

Abstract: Petrochemical pharmaceutical bio-fermentation industry, witch is characterized by the production press of the material inside the device sets experiencing recessive chemical processes. In industrial production process, some media usually easy to produce large foam, witch affect production, it must be detected the amount of foam in real time, to effectively eliminate the foam bubbles and control the processes of the physical and chemical reactions to ensure the efficient, orderly and safe conduct throughout the process .Foam is multi-interface, uneven density and unstable surface shape, each bubble has its own gas and liquid interface, many bubbles overlap together, with the various interfaces. Staggered and different angles, witch making it light-scattering, in order to obtain a clear picture of foam, and effectively obtain features of foam, shoot on goal from different angles, the captured images are compared and analyzed to choose the best camera angle. Morphological methods was introduced and used to extract the edge of bubbles in foam. This work proposed a improved Hough Transform (HT) to analyze round bubbles and detect each bubble.To detect whether the captured image is the foam image, this work also proposed calculating the density of bubbles in the captured image. The preliminary results showed that the algorithm is dynamic with high efficient.

Abstract: In order to solve the defect detection problems of black line and white line of QR Code. According to the linear properties of defect, this paper puts forward a kind of defect detection algorithm based on Hough Transform and vertical projection. Through the experiment testing, the accuracy of algorithm detection reached 98.57%, the average test time is 38.28ms. This algorithm can be transplanted to other types of QR code and industrial on-line detection system.

Abstract: Automatic recognition of the line in the image is an important work in the field of machine vision and image processing. Focusing on the problem of the computational cost and large invalid sampling in the line extraction algorithm using standard Hough transform (HT). An improved HT algorithm is proposed to solve these problems. The parameters of the improved algorithm can be reduced to one and the accumulator is operated by setting the tolerance. Then the existence of linear is determined by seting the threshold. The experimental results show that the algorithm not only can effectively solve the problem of local maxima and improves the algorithm speed and reduces the storage space,but also the accuracy of line extraction is improved.

Abstract: In order to meet the trend and consumer demands for video information, the ISO/IEC group and ITU-T video encoding expert group have cooperated in making the new video encoding standard of HEVC. It defines 35 Intra prediction modes and thus has a very high encoding complexity. In order to reduce this complexity, this paper has proposed a new algorithm to effectively reduce the number of the candidate mode which needs to be checked. The edge detection and Hough transform are utilized for the prediction unit (PU) with different sizes. Statistical analysis is utilized for the detected edge line angles to decide the candidate modes that need to be checked. The C++ and OpenCV language have been utilized for the implementation of the proposed algorithm. The proposed algorithm can reduce the encoding time by 43.72 percent at most and 17.06 percent at least with just little increase of the code rate and small decrease of the PSNR.

Abstract: In this paper, we introduce a new method for ellipse detection. For any object has closed curve in a digital image, it is easy to calculate the centroid of the object. We assume the object is an ellipse, and then by rotating, scaling this object, it can be transformed to a circle. So, ellipse detection problem becomes circle detection problem. Compared with other detection methods, our method only need process border points of the object, hence has higher detection speed.

Abstract: In a condom sorting process, we need to shoot the state image of condom through the camera and do the ellipse detection to determine the front position of condom on the conveyor belt, so developing the image processing algorithms which can detect the condom ring is necessary. The algorithm based on the Hough circle detection can obtain better detection effect for the most forms of the condom ring position, but it can not correctly detect the circle when the image shows linear shape; the algorithm based on the contrast of the ring detection get better effect on the ring in the image showing linear, while it has a low recognition rate in more folded case. We combined the two algorithms to use, proposed a combined algorithm which overcame the respective shortcomings of the two algorithms. Verified by experiment, the results of detection, recognition rate and the average processing time show the combined algorithms get the best comprehensive effect.

Abstract: Hough Transform ^[ has become a common method in the usage of line detection because of its robustness. It is important in computer vision and image analysis. Usually, the standard Hough transform method (SHT) transform the points in image space into parameter space and vote for all the possible patterns passing through that point. But, there are two serious problems in the standard method of line detection. The first is the high computation complexity and the second is the large storage requirements .In order to solve the two problems, this paper raise a fast-Hough transform algorithm base on pyramid algorithm. First of all we need to desample the primitive binary image with n times; and execute the Hough transform in the nth level image to get the parameter of straight line in this image, which is used in the n-1 level image. Finally we can get the parameter of lines in the primitive image. Experiments show that this method can extremely reduces the computational time.