Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content search and geographical consideration techniques and system employed as part of a digital environment are described. In one or more implementations, a digital medium environment is described for configuring image searches by one or more computing devices. Data is received by the one or more computing devices that identifies images obtained by users and used as part of content creation, indicates geographical locations of respective said users that obtained the images or associated with the content that includes the images, and indicates times associated with the users as obtaining the images or use of the images as part of the content. A map is built by the one or more computing devices that describes how use of the images as part of the content creation is diffused over the geographical locations over the indicated times. An image search is controlled by the one or more computing devices based on the map and a geographic location associated with the image search.

Abstract: Image search persona techniques and systems are described. In one or more implementations, a digital medium environment is described for controlling image searches by one or more computing devices. An image search request and an indication of one or more personas of one or more respective users associated with the image search request is received by the one or more computing devices. The one or more personas specify characteristics of the one or more respective users themselves. A plurality of images are obtained by the one or more computing devices based on the image search request. The plurality of images are filtered by the one or more computing devices based on the one or more personas and a search result is generated by the one or more computing devices from the filtered plurality of images.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Usage based content search result techniques are described. In one or more implementations, a digital medium environment controls image searches and availability by one or more computing devices. A search is performed by the one or more computing devices to locate images made available via a network by a content sharing service responsive to one or more inputs received from a user. A search result is configured by the one or more computing devices that includes the plurality of images based at least in part on an amount of usage of respective said images by other users of the content sharing service. Output of the search result is controlled via a user interface by the one or more computing devices to the user of the content sharing service.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Usage based content search result techniques are described. In one or more implementations, a digital medium environment controls image searches and availability by one or more computing devices. A search is performed by the one or more computing devices to locate images made available via a network by a content sharing service responsive to one or more inputs received from a user. A search result is configured by the one or more computing devices that includes the plurality of images based at least in part on an amount of usage of respective said images by other users of the content sharing service. Output of the search result is controlled via a user interface by the one or more computing devices to the user of the content sharing service.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Image search persona techniques and systems are described. In one or more implementations, a digital medium environment is described for controlling image searches by one or more computing devices. An image search request and an indication of one or more personas of one or more respective users associated with the image search request is received by the one or more computing devices. The one or more personas specify characteristics of the one or more respective users themselves. A plurality of images are obtained by the one or more computing devices based on the image search request. The plurality of images are filtered by the one or more computing devices based on the one or more personas and a search result is generated by the one or more computing devices from the filtered plurality of images.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Content search and geographical consideration techniques and system employed as part of a digital environment are described. In one or more implementations, a digital medium environment is described for configuring image searches by one or more computing devices. Data is received by the one or more computing devices that identifies images obtained by users and used as part of content creation, indicates geographical locations of respective said users that obtained the images or associated with the content that includes the images, and indicates times associated with the users as obtaining the images or use of the images as part of the content. A map is built by the one or more computing devices that describes how use of the images as part of the content creation is diffused over the geographical locations over the indicated times. An image search is controlled by the one or more computing devices based on the map and a geographic location associated with the image search.

Abstract: One embodiment of the present invention provides a system that removes noise from an image. During operation, the system first identifies blobs in the image, wherein a blob is a set of contiguous pixels which possibly represents a character or a portion of a character in the image. Next, the system analyzes the blobs to dynamically determine a “noise threshold” for the blobs. The system then removes blobs from the image which are below the noise threshold.

Abstract: A method identifying a ligature within a scanned document, the ligature including two or more touching characters. The two or more touching characters of the ligature are then compared to a plurality of prototypes to identify two or more matched prototypes. A synthetic ligature is then created based on the two or more matched prototypes.

Abstract: One embodiment of the present invention provides a system that removes noise from an image. During operation, the system first identifies blobs in the image, wherein a blob is a set of contiguous pixels which possibly represents a character or a portion of a character in the image. Next, the system analyzes the blobs to dynamically determine a “noise threshold” for the blobs. The system then removes blobs from the image which are below the noise threshold.