31 results about "Scale-space segmentation" patented technology

The invention brings forward a Chinese word segmentation method by using character embedding based on word context and a neural network. The character embedding is learnt on large-scale automatic segmentation of data. The learnt character embedding is used as inputting of a segmentation model of the neural network so as to effectively help model learning. The method comprises the concrete steps of learning character embedding on large-scale automatic segmentation of data according to the word context and lexeme marking; and utilizing character-embedding as inputting of the segmentation model of the neural network so that segmentation performance is improved. Compared with other Chinese word segmentation method technologies based on the neural network, the method adopts the character-embedding technology based on the word context so that word information is effectively integrated into the segmentation model. Therefore, the accuracy of a word segmentation task is improved.

Advanced driver assistance systems need to be able to recognize and to classify traffic signs under real time constraints, and under a wide variety of visual conditions. The invention shown employs binary masks extracted by color space segmentation, with a different binary mask generated for each sign shape. Temporal tracking is employed to add robustness to the detection system. The system is generic, and is trainable to the signs used in various countries.

The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image color enhancing method based on multi-scale image segmentation and color transferring. The method comprises steps: S1, conducting wavelet denoising preprocessing for a target gray level image; S2, according to a multi-scale normalized segmentation method, conducting segmentation of the target gray level image after preprocessed; S3, combining a reference image, and conducting brightness matching for all sub-domains of the target gray level image; and S4, selecting a sub-domain with the similar property to conduct mapping and color transferring. Aesthetic measure and target recognized degree of a result image are obviously enhanced, under the condition that image registering is not needed, the method can achieve full-automatic color enhancing for a remote sensing image which is relatively simple in texture structure and big in brightness contrast just through a color reference image which is similar in character and style, and therefore, the remote sensing image color enhancing method provides strong technical support for remote sensing image processing.

The invention provides a high-performance implementation method for multi-scale segmentation of remote sensing images, and in particular a method for implementing fast and multi-scale image segmentation of large amount of remote sensing images and establishing the structural relationship of segmentation results in the process of high-resolution remote sensing image information extraction. The method comprises the following steps: on the basis of analyzing the implementation procedure of the algorithm and finding out the computing-intensive segment of the algorithm, realizing the parallel segmentation of the algorithm-intensive segment based on MPI and OMP models, and carrying out date join on the parallel segmentation results; implementing the multi-scale image segmentation by storing theinitial segmentation results of the algorithm and merging the subsequent multi-scale remote sensing images; and establishing a multi-scale object topological relation model. The generated multi-scalesegmentation region and corresponding hierarchical relationship can be applied to various services; and the corresponding implementation method is applicable to various segmentation algorithms such as mean shift and the like, and can greatly improve the data amount processed by algorithm and the processing efficiency.