METHOD AND SYSTEM OF IDENTIFYING AN ENTITY FROM A DIGITAL IMAGE OF A PHYSICAL TEXT
A method of identifying an entity from text in a digital image includes the step of obtaining a digital image. The digital image includes a digital photograph of a physical text. At least a portion of the physical text is related to a pre-defined topic. The digital photograph of the physical text is converted to a text in a computer-readable format. A word dictionary is provided. The word dictionary includes a set of words related to the pre-defined topic. A set of words of matching the text to similar words in the set of words in the word dictionary. A word cluster in the text is identified. Each word in the word cluster is associated with a category of a single entity. The single entity is a member of a class of entities demarcated by the pre-defined topic. A database including a list of members of the class of entities demarcated by the pre-defined topic is search for one or more entities matching one or more of word-category associations of the word cluster.
1 . A method of identifying an entity from text in a digital image comprising:
obtaining a digital image, wherein the digital image comprises a digital photograph of a physical text, wherein at least a portion of the physical text is related to a pre-defined topic;
converting the digital photograph of the physical text to a text in a computer-readable format;
providing a word dictionary, wherein the word dictionary comprises a set of words related to the pre-defined topic;
matching a set of words of the text to similar words in the set of words in the word dictionary;
identifying a word cluster in the text, wherein each word in the word cluster is associated with a category of a single entity, wherein the single entity is a member of a class of entities demarcated by the pre-defined topic; and
searching a database comprising a list of members of the class of entities demarcated by the pre-defined topic for one or more entities matching one or more of word category associations of the word cluster.
2 . The method of claim 1 further comprises:
receiving a user instruction that identifies the word cluster.
3 . The method of claim 1 , wherein the digital image is obtained with a digital camera system in a mobile device of a user.
4 . The method. of claim 2 , wherein the step of matching a set of words of the text to similar words in the set of words related to the pre-defined topic further comprises:
implementing a linear n-gram scanning processes to convert a set of character strings of each word in the set of words of the text to words related to the pre-defined topic according to a statistical algorithm.
5 . The method of claim 3 , wherein the class of entities demarcated by the pre-defined topic comprises a set of wine items.
6 . The method of claim 5 , wherein the digital image comprises a digital photograph of wine menu.
7 . The method of claim 6 , wherein a set of categories of the wine item comprises a varietal, a producer and a vintage.
8 . The method of claim 7 wherein the word cluster is identified based on a set of pre-defined rules for determining that each word in the word cluster is related to a category.
9 . The method of claim 8 , wherein set of pre-defined rules comprises a vintage rule that allows for only a single vintage-related word to define a vintage category of the set of wine items.
10 . The method of claim 2 , wherein the set of rules are based on a prior knowledge of normative layout of an entity type on a physically-printed text.
11 . The method of claim 2 further comprising:
returning, a sorted list of the one or more entities matching the one or more of word-category associations of the word cluster, wherein in the list is ranked based on the number of matches between the word-category associations of the word cluster for each entity in the list.
12 . A computerized system of identifying an entity from text in a digital image comprising:
a processor configured to execute instructions;
a memory including instructions when executed on the processor, causes the processor to perform operations that:
obtain a digital image, wherein the digital image comprises a digital photograph of a physical text, wherein at least a portion of the physical text is related to a pre-defined topic;
convert the digital photograph of the physical text to a text in a computer-readable format;
provide a word dictionary, wherein the word dictionary comprises a set of words related to the pre-defined topic;
match a set of words of the text to similar words in the set of words in the word dictionary;
identify a word cluster in the text, wherein each word in the word cluster is associated with a category of a single entity, wherein the single entity is a member of a class of entities demarcated by the pre-defined topic; and
search a database comprising a list of members of the class of entities demarcated by the pre-defined topic for one or more entities matching one or more of word-category associations of the word cluster.
13 . The computerized system of claim 12 , wherein the memory including instructions when executed on the processor, causes the processor to perform operations that:
receive a user instruction that identifies the word cluster;
return a sorted list of the one or more entities matching the one or more of word-category associations of the word cluster, wherein in the list is ranked based on the number of matches between the word-category associations of the word cluster for each entity in the list; and
implement a linear n-gram scanning processes to convert a set of character strings of each word in the set of words of the text to words related to the pre-defined topic according to a statistical algorithm.
14 . The computerized system of claim 13 , wherein the digital image is obtained with a digital camera system in a mobile device of a user.
15 . The computerized system of claim 14 , wherein the class of entities demarcated by the pre-defined topic comprises a set of wine items,
16 . The computerized system of claim 15 , wherein the digital image comprises a digital photograph of a wine menu.
17 . The computerized system of claim 16 , wherein a set of categories of the vine item comprises a varietal, a producer and a vintage.
18 . The computerized system of claim 17 , wherein the word cluster is identified based on a set of pre-defined rules for determining, that each word in the word cluster is related to a category.
19 . The computerized system of claim 18 , wherein set of pre-defined rules comprises a vintage rule that allows for only a single vintage-related word to define a vintage category of the set of wine items.
20 . The computerized system of claim 19 , wherein the set of rules are based on a prior knowledge of a normative layout of an entity type on a physically-printed text.