A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to ...A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to bad and complex environmental conditions.The bounding-box of the logo is extracted by a thershloding approach.Experimental results show that 93.58% location accuracy is achieved with 1100 images under various environmental conditions,indicating that the proposed method is effective and suitable for the location of vehicle logo in practical applications.展开更多
Besides their decorative purposes,vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information retrieval.However,unlike the ...Besides their decorative purposes,vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information retrieval.However,unlike the license plate,which is designed for identification purposes,vehicle manufacturer logos are mainly designed for decorative purposes such that they might lack discriminative features themselves.Moreover,in practical applications,the vehicle manufacturer logos captured by a fixed camera vary in size.For these reasons,detection and recognition of vehicle manufacturer logos are very challenging but crucial problems to tackle.In this paper,based on preparatory works on logo localization and image segmentation,we propose a size-self-adaptive method to recognize vehicle manufacturer logos based on feature extraction and support vector machine(SVM)classifier.The experimental results demonstrate that the proposed method is more effective and robust in dealing with the recognition problem of vehicle logos in different sizes.Moreover,it has a good performance both in preciseness and speed.展开更多
文摘A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to bad and complex environmental conditions.The bounding-box of the logo is extracted by a thershloding approach.Experimental results show that 93.58% location accuracy is achieved with 1100 images under various environmental conditions,indicating that the proposed method is effective and suitable for the location of vehicle logo in practical applications.
基金supported by the National High Technology Research and Development Program of China (No.2007AA01Z417)the 111 Project (No.B08004).
文摘Besides their decorative purposes,vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information retrieval.However,unlike the license plate,which is designed for identification purposes,vehicle manufacturer logos are mainly designed for decorative purposes such that they might lack discriminative features themselves.Moreover,in practical applications,the vehicle manufacturer logos captured by a fixed camera vary in size.For these reasons,detection and recognition of vehicle manufacturer logos are very challenging but crucial problems to tackle.In this paper,based on preparatory works on logo localization and image segmentation,we propose a size-self-adaptive method to recognize vehicle manufacturer logos based on feature extraction and support vector machine(SVM)classifier.The experimental results demonstrate that the proposed method is more effective and robust in dealing with the recognition problem of vehicle logos in different sizes.Moreover,it has a good performance both in preciseness and speed.
