Systems and methods for identifying salient images

#This disclosure relates to identifying salient images based on size, amount, and histogram within salient regions of images.

#Manually identifying salient portions of images/salient images for image/video processing may be time consuming. Quickly and efficiently identifying salient portions of images/salient images may encourage users to capture/view/edit images/videos.

#This disclosure relates to identifying salient images. Image information defining an image may be accessed. The image may include one or more salient objects. A saliency map may be generated based on the image information. The saliency map may include one or more regions corresponding to the one or more salient objects. The one or more regions may be characterized by different (e.g., higher) levels of intensity than other regions of the saliency map. One or more salient regions around the one or more salient objects may be identified based on the saliency map. A saliency metric for the image may be generated based on one or more of (1) sizes of the one or more salient regions; (2) an amount of the one or more salient regions; and/or (3) histograms within the one or more salient regions.

#FIG. 1 illustrates a system that identifies salient images.

#FIG. 2 illustrates a method for identifying salient images.

#FIG. 3 illustrates an example image.

#FIG. 1 illustrates a system 10 for identifying salient images. The system 10 may include one or more of a processor 11, an electronic storage 12, an interface 13 (e.g., bus, wireless interface), and/or other components. Image information defining an image may be accessed by the processor 11. The image may include one or more salient objects. A saliency map may be generated based on the image information. The saliency map may include one or more regions corresponding to the one or more salient objects. The one or more regions may be characterized by different (e.g., higher levels) of intensity than other regions of the saliency map. One or more salient regions around the one or more salient objects may be identified based on the saliency map. A saliency metric for the image may be generated based on one or more of (1) sizes of the one or more salient regions; (2) an amount of the one or more salient regions; and/or (3) histograms within the one or more salient regions.

#The electronic storage 12 may be configured to include electronic storage medium that electronically stores information. The electronic storage 12 may store software algorithms, information determined by the processor 11, information received remotely, and/or other information that enables the system 10 to function properly. For example, the electronic storage 12 may store information relating to image information, images, video frames, video content, salient objects, saliency regions, saliency metrics, and/or other information.

#Referring to FIG. 1, the processor 11 may be configured to provide information processing capabilities in the system 10. As such, the processor 11 may comprise one or more of a digital processor, an analog processor, a digital circuit designed to process information, a central processing unit, a graphics processing unit, a microcontroller, an analog circuit designed to process information, a state machine, and/or other mechanisms for electronically processing information. The processor 11 may be configured to execute one or more machine readable instructions 100 to facilitate identifying salient images. The machine readable instructions 100 may include one or more computer program components. The machine readable instructions 100 may include one or more of an image information component 102, a salient map component 104, a saliency region component 106, a saliency metric component 108, and/or other computer program components.