Automatic method of generating thematic summaries from a document image without performing character recognition

Claim 2

A processor implemented method of generating a thematic summary of a document image without performing character recognition using a processor, the document including a first multiplicity of sentences and a second multiplicity of word occurrences, the processor implementing the method by executing instructions stored in electronic form in a memory coupled to the processor, the processor implemented method comprising the steps of: a) analyzing the document image to identify sentence boundaries; b) analyzing the document image to identify a plurality of word image equivalence classes, each word image equivalence class including at least one word occurrence of the second multiplicity of word occurrences; c) selecting as thematic word images a first number of word image equivalence classes, the first number being less than a second number of thematic sentences to be extracted; d) scoring each sentence of the first multiplicity of sentences based upon occurrence of thematic word images in each sentence; and e) selecting the second number of thematic sentences from the first multiplicity of sentences based upon the score of each sentence.

Claim 3

The processor implemented method of claim 1 further comprising the step of: f) presenting images of the thematic sentences to the user of the processor in an order in which the thematic sentences occur in the document image.

Claim 4

The processor implemented method of claim 1 wherein step d) comprises incrementing the score of each sentence for each thematic word image occurring in the sentence by an amount related to the frequency of occurrence of the thematic word image within the document.

Claim 5

The method of claim 1 prior to step c) further comprising the steps of: d) receiving the second number from an input device coupled to the processor.

Claim 6

The processor implemented method of claim 4 wherein the first number is at least three.

Claim 7

A processor implemented method of generating a thematic summary of a document image without performing character recognition using a processor, the document including a first multiplicity of sentences and a second multiplicity of word occurrences, the processor implementing the method by executing instructions stored electronically in a memory coupled to the processor, the processor implemented method comprising the steps of: a) analyzing the document image to identify sentence boundaries of the first multiplicity of sentences; b) analyzing the document image to identify a plurality of word image equivalence classes, each word image equivalence class including at least one word occurrence of the second multiplicity of word occurrences, each word image equivalence class having a bounding box, each bounding box having a width; c) determining a number of times each word image equivalence class occurs in the document; d) identifying drop words within the word image equivalence classes based upon their bounding box width and the number of times each word image equivalence class occurs in the document; e) generating a list of content words by eliminating the drop words from the word image equivalence classes; f) selecting as thematic word images a first number of the word equivalence classes from the list of content words based upon the number of times each content word occurs in the document; g) scoring each sentence of the first multiplicity of sentences that includes a thematic word image based upon occurrences of thematic word images within each sentence; and h) selecting as thematic sentences a second number of the first multiplicity of sentences based upon the sentence scores.

Claim 8

A processor implemented method of generating a thematic summary of a document image without performing character recognition using a processor, the document including a first multiplicity of sentences and a second multiplicity of word occurrences, the processor implementing the method by executing instructions stored electronically in a memory coupled to the processor, the processor implemented method comprising the steps of: a) analyzing the document image to identify sentence boundaries of the first multiplicity of sentences; b) analyzing the document image to identify a plurality of word image equivalence classes, each word image equivalence class including at least one word occurrence of the second multiplicity of word occurrences, each word image equivalence class having a bounding box, each bounding box having a width; c) determining a number of times each word image equivalence class occurs in the document; d) identifying drop words within the word image equivalence classes based upon their bounding box width and the number of times each word image equivalence class occurs in the document; e) generating a list of content words by eliminating the drop words from the word image equivalence classes; f) selecting as thematic word images a first number of the word equivalence classes from the list of content words based upon the number of times each content word occurs in the document; g) scoring each sentence of the first multiplicity of sentences that includes a thematic word image based upon occurrences of thematic word images within each sentence; and h) selecting as thematic sentences a second number of the first multiplicity of sentences based upon the sentence scores.

Claim 9

The computer implemented method of claim 6 wherein step g) comprises incrementing the score of each sentence for each thematic word image occurring in the sentence by an amount related to the frequency of occurrence of the thematic word image within the document.

Claim 10

The method of claim 6 prior to step f) further comprising the steps of: i) receiving the second number from an input device coupled to the processor.

Claim 11

The processor implemented method of claim 8 wherein the first number is at least three.

Claim 12

The processor implemented method of claim 6 wherein step d) comprises identifying drop word images based upon the number of times each word image equivalence class appears as a first non-short word in a sentence of the first multiplicity of sentences.

Claim 13

An article of manufacture comprising: a) a memory; and b) instructions stored in the memory for a method of generating a thematic summary of a document image without performing character recognition using a processor coupled to the memory, the document including a first multiplicity of sentences and a second multiplicity of word occurrences, the method comprising the steps of: 1) analyzing the document image to identify sentence boundaries; 2) analyzing the document image to identify word image equivalence classes, each word image equivalence class including at least one word occurrence of the second multiplicity of word occurrences; 3) selecting as thematic word images a first number of word image equivalence classes, the first number of thematic word images being less than a second number of thematic sentences to be extracted; 4) scoring each sentence of the first multiplicity of sentences based upon occurrence of thematic word images in each sentence; and 5) selecting the second number of thematic sentences from the first multiplicity of sentences based upon the score of each sentence.

Claim 14

An article of manufacture comprising: a) a memory; and b) instructions stored in the memory for a method of generating a thematic summary of a document image without performing character recognition using a processor coupled to the memory, the document including a first multiplicity of sentences and a second multiplicity of word occurrences, the method comprising the steps of: 1) analyzing the document image to identify sentence boundaries; 2) analyzing the document image to identify word image equivalence classes, each word image equivalence class including at least one word occurrence of the second multiplicity of word occurrences; 3) selecting as thematic word images a first number of word image equivalence classes, the first number of thematic word images being less than a second number of thematic sentences to be extracted; 4) scoring each sentence of the first multiplicity of sentences based upon occurrence of thematic word images in each sentence; and 5) selecting the second number of thematic sentences from the first multiplicity of sentences based upon the score of each sentence.