Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain.These include the scale-invariant feature transform algorithm,speed...Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain.These include the scale-invariant feature transform algorithm,speeded-up robust features algorithm,binary robust invariant scalable keypoints algorithm,and oriented fast and rotated brief algorithm.The performance of these algorithms was estimated in terms of matching accuracy,feature point richness,and running time.The experiment result showed that no algorithm achieved high accuracy while keeping low running time,and all algorithms are not suitable for image feature extraction and matching of augmented solar images.To solve this problem,an improved method was proposed by using two-frame matching to utilize the accuracy advantage of the scale-invariant feature transform algorithm and the speed advantage of the oriented fast and rotated brief algorithm.Furthermore,our method and the four representative algorithms were applied to augmented solar images.Our application experiments proved that our method achieved a similar high recognition rate to the scale-invariant feature transform algorithm which is significantly higher than other algorithms.Our method also obtained a similar low running time to the oriented fast and rotated brief algorithm,which is significantly lower than other algorithms.展开更多
Image matching based on scale invariant feature transform（SIFT） is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are genera...Image matching based on scale invariant feature transform（SIFT） is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT.展开更多
Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage...Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.展开更多
基金Supported by the Key Research Program of the Chinese Academy of Sciences(ZDRE-KT-2021-3)。
文摘Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain.These include the scale-invariant feature transform algorithm,speeded-up robust features algorithm,binary robust invariant scalable keypoints algorithm,and oriented fast and rotated brief algorithm.The performance of these algorithms was estimated in terms of matching accuracy,feature point richness,and running time.The experiment result showed that no algorithm achieved high accuracy while keeping low running time,and all algorithms are not suitable for image feature extraction and matching of augmented solar images.To solve this problem,an improved method was proposed by using two-frame matching to utilize the accuracy advantage of the scale-invariant feature transform algorithm and the speed advantage of the oriented fast and rotated brief algorithm.Furthermore,our method and the four representative algorithms were applied to augmented solar images.Our application experiments proved that our method achieved a similar high recognition rate to the scale-invariant feature transform algorithm which is significantly higher than other algorithms.Our method also obtained a similar low running time to the oriented fast and rotated brief algorithm,which is significantly lower than other algorithms.
基金supported by the National Natural Science Foundation of China(61271315)the State Scholarship Fund of China
文摘Image matching based on scale invariant feature transform（SIFT） is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT.
基金Project(61725306)supported by the National Science Foundation for Distinguished Young Scholars of ChinaProjects(61473318,61403136,61703157,61751312)supported by the National Natural Science Foundation of ChinaProject(16C0940)supported by Foundation of Hunan Educational Committee,China
文摘Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.
