A patent application filed by Google with the World Intellectual Property Organization in June 2007 and published on Thursday points to more sophisticated search techniques.

　　The filing suggests that the privacy issues raised by Google Maps Street View will only get more complicated, that YouTube searchers may one day be able to conduct keyword searches for text captured on video, and that Google searches may one day return a list of products on local store shelves.

　　“Recognizing Text In Images” is an application to patent a method of optical character recognition in digital images.

　　“Digital images can include a wide variety of content,” the patent application explains. “For example, digital images can illustrate landscapes, people, urban scenes, and other objects. Digital images often include text. Digital images can be captured, for example, using cameras or digital video recorders. Image text (i.e., text in an image) typically includes text of varying size, orientation, and typeface. Text in a digital image derived, for example, from an urban scene (e.g., a city street scene) often provides information about the displayed scene or location. A typical street scene includes, for example, text as part of street signs, building names, address numbers, and window signs.”

　　The image database behind Google Maps Street View happens to contain many street scenes of with this sort of text. Being able to query for store names captured in Street View photos might be a useful way to conduct local searches.

　　A spokesperson for Google said in an e-mail, “…[W]e file patent applications on a variety of ideas that our employees come up with. Some of those ideas later mature into real products or services; some don’t. Prospective product announcements should not necessarily be inferred from our patent applications.”

　　It is however worth noting the backgrounds of Luc Vincent and Adrian Ulges, the two computer scientists behind the patent applications. Vincent describes himself on his Web site as “[l]eader of several large geo-related projects, including Street View”, as being “[r]esponsible for various engineering aspects of Google Book Search,” and as the “[h]ead of Google OCR-related initiatives.” Ulges on his Web site notes his involvement in helping to develop “a system that autonomously learns to tag videos with high-level semantic concepts by watching videos from online portals like http://youtube.com.”

　　The patent application envisions several possible advantages arising from the technology. “Candidate text regions within images can be enhanced to improve text recognition accuracy,” the patent application states. “Extracted image text can also be used to improve image searching. The extracted text can be stored as associated with the particular image for use in generating search results in an image search. Additionally, the extracted image text can be combined with location data and indexed to improve and enhance location-based searching. The extracted text can provide keywords for identifying particular locations and presenting images of the identified locations to a user.”

　　Google of course contemplates using the technology to add value to its search advertising business. “For example, a user enters a search for a McDonald’s in a particular city or near a particular address,” the patent application suggests. “The mapping application generates a map to the McDonald’s as well as presents an image of the McDonald’s. The McDonald’s image is retrieved using the indexed text from the image identifying the McDonald’s and location information associated with the image, which identifies the location of the particular McDonald’s in the image.”

　　But Google also imagines novel uses. Just as Google created Street View by having camera-equipped vehicles drive through urban areas to capture a series of images of the trip, the search giant imagines cruising the aisles of supermarkets with camera-equipped robots to create what might be called Google Product View. “In one implementation, a store (e.g., a grocery store or hardware store) is indexed,” the patent application explains. “Images of items within the store are captured, for example, using a small motorized vehicle or robot. The aisles of the store are traversed and images of products are captured in a similar manner as discussed above. Additionally, as discussed above, location information is associated with each image. Text is extracted from the product images. In particular, extracted text can be filtered using a product name database in order to focus character recognition results on product names.”

　　Such possibilities of course remain highly speculative, and may, like the non-existent but presumably longed-for Google Perp Locator or Google Babe/Stud Finder, never come to pass.

　　Google于2007年6月向世界知识产权组织提交了一项专利申请，而该专利“识别图片文字”是采用识别数字图片的光学特点的方法，将使Google的搜索技术更加强大，在1月3日获得了批准。

　　目前，Google在Google地图街景中秘密使用了该项技术。YouTube搜索者可以用视频中的文字为关键字进行检索，而且Google搜索者也可能得到当地商店的货架产品清单上。

　　专利申请中解释“数字图片包括多种多样的信息，例如数字图片有风景、人像、街景和其他对象。数字图片中常常含有文字，并具有复杂的大小、方位和字体。导出图片中的文字，例如从一张街景图片中，则可以获得相关的信息，如典型街景包括街牌号、建筑名、邮政编码等。”

　　Google地图街景中的图片数据库正好包含大量含有文字的街景，识别图片文字将有助于本地搜索。，而该专利由两位计算机科学家——Luc Vincent和Adrian Ulges共同开发。

　　展望未来，该专利的技术将带来一些可能的进步，如提取图片中的文字可用来提高图片搜索的质量，还能够与本地数据核对来提高本地搜索的质量。图片中的文字提供了验证本地特征的关键字，并且能够告诉用户图片所表述的位置。

　　Google将会打算使用这项技术提高广告业务的质量，如用户搜索某个城市或附近的麦当劳餐厅，地图系统在搜索麦当劳的图片时，同时产生麦当劳的分布地图，麦当劳相关的图片将通过文字进行验证，同时也验证该图片的地址，从而得出某个麦当劳餐厅的所在。