42results about How to "Solve misidentification" patented technology

The invention discloses a fast get-in and get-out toll collection system for highway and a working method of the fast get-in and get-out toll collection system. The fast get-in and get-out toll collection system comprises a network payment platform, a highway entrance server, a lane camera, a lane controller, a fast gateway, a service management server, a database server and a highway exist server, wherein the highway entrance server and the highway exist server have functions of automatically identifying license plate and vehicle model information, and also have a function of manually inputting the license plate information, namely a function of manually inputting the number of a license plate by virtue of a keyboard or a mouse. The fast get-in and get-out toll collection system for highway disclosed by the invention can be used for realizing non-stop electronic toll collection of the highway by virtue of prepayment electronic payment means. A prepayment account is opened within several minutes by virtue of a network way, so that the trend of the internet finance is satisfied, the consumption concept of a car owner, especially a young car owner, is satisfied, and the popularization is easy. All entrances and exits of an MTC (manual toll collection system) of the highway have fast traffic capacity with non-stop electronic toll collection. The fast get-in and get-out toll collection system for highway disclosed by the invention can be used for saving a great deal of IC (integrated circuit) acquisition expenses of the highway.

The present invention relates to a three-lane detection method based on image morphological segmentation and region growing. The method comprises: a method for, by using a shape of a lane mark and a relative gray level of a roadway, performing segmentation on the lane mark by means of image morphology; a method for fitting a vanishing point by using a weighted least square method; and a method for forming a region of interest (ROI) of the lane mark by a region growing method and iteratively searching for a feature point of the lane mark. According to the three-lane detection method based on image morphological segmentation and region growing, aimed at the problem of perception of a vehicle-mounted visual system of an intelligent vehicle to a multi-lane road in a process of driving on the urban structural multi-lane road, a method of carrying out image morphology preprocessing and carrying out iterative solution on the lane mark is adopted to adapt to a multi-lane environment. The method is novel in algorithm, high in adaptability, relatively high in illumination robustness, small in computation amount and easy to implement by programming, so that a module of the vehicle-mounted visual system is improved, and the efficiency and environmental adaptability of an intelligent vehicle environment sensing module are further improved.

The invention provides a license plate character global recognition method based on a deep learning model. The license plate character global recognition method comprises the steps of: step a, performing vehicle detection to obtain a target vehicle, and determining an entire license plate detection region by means of the target vehicle; step b, performing detection in the entire license plate detection region to obtain a license plate region; step c, and performing global recognition on the license plate region by means of a deep neural network model, wherein the deep neural network model comprises four convolutional layers and two full-connection layers which are connected in sequence, the last full-connection layer comprises seven branches, and the branches correspond to Chinese characters, letters, numbers or identifiers on license plate numbers separately. The license plate character global recognition method improves the license plate character recognition rate through introducing the deep learning model for global recognition, and overcomes the error recognition problem caused by the dependence and result uncertainty when a traditional license plate recognition method needs to segment license plate characters.

The invention discloses a recognition method and device for a real plane in an image and a mobile terminal, and belongs to the technical field of computer application. The method comprises the following steps of: obtaining a sample; obtaining a pixel coordinate collected by a depth camera and a corresponding depth value; calculating world coordinates according to the pixel coordinates and the depth values; A random sampling consistency algorithm is adopted to carry out segmentation calculation on the world coordinates, a real plane in the image is extracted, and image information does not needto be prepared in advance during real plane recognition, so that the recognition efficiency of the real plane is effectively improved, the problem of image false recognition is avoided, and the accuracy of image recognition is improved.

The invention is suitable for the field of image identification, and provides a method and device for feature matching and an image identification device. The method includes the steps that features obtained at a time point are stored in one sub-model-bank, after the sub-model-banks are added into a model bank, the features of the sub-model-banks added each time only need to be mapped into corresponding Hash addresses of a Hash table, when a tested bank needs to be matched with the model bank, newly-added sub-tested-banks are firstly mapped into corresponding Hash addresses of the Hash table, then features of the sub-tested-banks are matched with the features in the mapped Hash addresses, and the matching results can be obtained. Compared with the prior art, the method, the device and the image identification device have the advantages that when matching is carried out each time, the whole model bank does not need to be mapped into corresponding Hash addresses of the Hash table, the spent time is short, and the matching efficiency is easily improved; in addition, matching is carried out according to the Hash function, wrong identification generated when a Brun filter is adopted can be avoided, and the matching accuracy is high.

The invention relates to the technical field of remote sensing data analysis and remote sensing data identification, and discloses a continuous storm event intelligent identification early warning method, which comprises the following steps: obtaining remote sensing information in a monitoring area range, obtaining the significant wave height of an ocean area according to remote sensing data, and obtaining a first target area; and obtaining the surface temperature of the region in the first target region set according to the remote sensing data, determining a storm threat region, and giving an alarm to the storm threat region. According to the invention, automatic identification and early warning of the continuous storm are realized, the early warning information is obtained according to the storm information of the beach, and the hysteresis of dependence on artificial experience in the prior art is overcome.

The invention discloses a hierarchical multi-source data fusion method for a pipeline linkage monitoring network, which comprises the following steps: carrying out data level preprocessing for various primary linkage detection signals acquired by a sensor at a common node of the monitoring network by using wavelet transformation, and extracting leakage-sensitive characteristic parameters; establishing a characteristic level data fusion model based on an ant colony neural network, processing the leakage characteristic parameters extracted by various sensors on the node, and constructing an elementary probability assignment function of evidence according to the output result of the ant colony neural network; and carrying out evidence synthesis at a cluster-head node according to an evidencecombination rule, and making final decisions according to a maximum trust value method. The invention provides the hierarchical multi-source linkage detection data fusion method from the data level and characteristic level to decision level, and solves the multi-source data processing problem of the pipeline linkage monitoring network; and the method utilizes the linkage detection information acquired by various sensors in the network so as to effectively improve the accuracy rate of leakage identification.

The invention discloses a fast get-in and get-out toll collection system for highway and a working method of the fast get-in and get-out toll collection system. The fast get-in and get-out toll collection system comprises a network payment platform, a highway entrance server, a lane camera, a lane controller, a fast gateway, a service management server, a database server and a highway exist server, wherein the highway entrance server and the highway exist server have functions of automatically identifying license plate and vehicle model information, and also have a function of manually inputting the license plate information, namely a function of manually inputting the number of a license plate by virtue of a keyboard or a mouse. The fast get-in and get-out toll collection system for highway disclosed by the invention can be used for realizing non-stop electronic toll collection of the highway by virtue of prepayment electronic payment means. A prepayment account is opened within several minutes by virtue of a network way, so that the trend of the internet finance is satisfied, the consumption concept of a car owner, especially a young car owner, is satisfied, and the popularization is easy. All entrances and exits of an MTC (manual toll collection system) of the highway have fast traffic capacity with non-stop electronic toll collection. The fast get-in and get-out toll collection system for highway disclosed by the invention can be used for saving a great deal of IC (integrated circuit) acquisition expenses of the highway.

Disclosed is a method for assigning packet data to be transmitted to a radio packet data channel of a base station system in response to a packet traffic transmission request for a plurality of mobile stations in a mobile communication system. The method comprises collecting the packet traffic transmission requests of the radio packet data channel for the mobile stations; selecting at least one of the mobile stations from the collected packet traffic transmission requests; transmitting to the selected mobile station a channel assignment message including information about a data rate, data transmission durations of the radio packet data channel and start points of the data transmission durations for the selected mobile station; and transmitting the packet data to the selected mobile station at the start time of the data transmission durations at the data rate.

The invention relates to a serial differential non-return-to-zero code identification method. Based on the logical or non-operational results of two differential signals corresponding to the serial differential non-return-to-zero code, a new identification method is designed, and each falling edge position of the result is used as Each start mark position, combined with the preset n times of the serial differential non-return-to-zero code frequency, as the clock frequency, samples the two differential signals separately, and then decodes to obtain the data corresponding to the serial differential non-return-to-zero code Value, so using the sampling judgment and storage of the digital circuit, the identification of the serial differential non-return-to-zero code can be realized, the control logic is simple and effective; and the entire identification method is stable and reliable, with small errors. , it only needs a simple falling edge judgment to correctly identify the code value and output the correct data. It has the characteristics of stable and reliable performance and small recognition error.

The embodiment of the present application discloses a vein identification method and related products. The method includes: acquiring a first vein image of a first part to be identified; performing first vein matching based on the first vein image to obtain a first matching value; Determine a second part to be identified and an image acquisition strategy corresponding to the second part to be identified based on the first vein image and the first matching value; acquire the first part of the second part to be identified based on the image acquisition strategy performing second vein matching based on the second vein image to obtain a second matching value; determining a vein recognition result based on the first matching value and the second matching value. The embodiments of the present application help to improve the accuracy of vein recognition.

The present invention is applicable to the field of image recognition, and provides a feature matching method, device and image recognition equipment. The method includes: a sub-pattern library stores features obtained at a time point, and after the sub-pattern library is added to the pattern library, It is only necessary to map the characteristics of each added sub-pattern library to the corresponding hash address of the hash table. When it is necessary to match the test library with the pattern library, first map the newly added sub-test library to the corresponding hash address of the hash table. Hash address, and then match the characteristics of the sub-test library with the characteristics in the mapped hash address to obtain the matching result. Compared with the prior art, the present invention does not need to map the entire pattern library to the corresponding hash address of the hash table every time the matching is performed, which consumes little time and is beneficial to improve the matching efficiency. Moreover, the use of the hash function for matching can avoid the problem of misidentification when using the Bron filter, and the matching accuracy is very high.

This application relates to the field of automatic driving, and discloses a method and system for identifying abnormal driving behavior and a vehicle including the system. The method for identifying abnormal driving behavior includes: acquiring vehicle driving behavior data, and judging whether the vehicle is in suspicious abnormal driving based on the vehicle driving behavior data The state of the behavior; if the vehicle is in the state of suspicious abnormal driving behavior, then obtain the current vehicle driving scene data; judge whether the suspicious abnormal driving behavior is abnormal driving behavior according to the vehicle driving behavior data and the current vehicle driving scene data; In the technical solution of the present application, the current driving scene information is introduced into the identification process of the abnormal driving behavior of the vehicle, which improves the accuracy of the identification of the abnormal driving behavior.