Method of locating image foreground by using LLC (Locality-constrained Linear Coding) criterion

Abstract

The invention relates to a method of locating an image foreground using LLC (Locality-constrained Linear Coding) criterion. A large number of random images are selected from a standard test set, in combination of the salient region truth value annotation graph, the priori knowledge of the image foreground is extracted, an LLC codebook is formed, the LLC criterion is used for carrying out rough classification on whether each area of a to-be-detected image belongs to the foreground, and a corresponding salience probability value is given; contrast-based features such as a centroid distance away from an image center, a local Lab color contrast value and a global Lab color contrast value are used for describing image super pixel regions, typical features for learning the foreground/background serve as the priori knowledge for guiding classification of the image super pixel regions, high-level knowledge is acquired from an empirical perspective, region classification can be guided for multiple times as long as one-time learning is needed, the foreground locating speed is greatly quickened compared with a method of extracting high-level knowledge only from the current image, and due to advantage query for extraction, the foreground boundary in the acquired salience map based on manifold ranking can be more clear and has less noise.

Description

technical field [0001] The invention relates to the fields of pattern recognition technology, information fusion technology, information coding technology and digital image processing technology, and specifically relates to a method for locating image foreground by using LLC criterion. Background technique [0002] Pattern recognition technology refers to the process of processing and analyzing various forms of (numerical, textual and logical) information representing things or phenomena to describe, identify, classify and explain things or phenomena. An essential part of science and artificial intelligence. Pattern recognition in saliency detection refers to the recognition and classification of background and objects in images. A salient target is a person or thing that stands out from the background in an image, and generally contains more interesting and useful information. The main task of salient object detection is to detect and mark the area where the salient objec...

AI Technical Summary

Problems solved by technology

On the other hand, when the image scene is complex, it is difficult for machine vision to detect the foreground from the cluttered background, resulting in the phenomenon of more noise near the foreground area and even blurred foreground boundaries in the saliency map generated by various advanced algorithms. The difficulty of foreground or object recognition

[0004] The posit...

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