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| 국가/구분 | United States(US) Patent 등록 |
|---|---|
| 국제특허분류(IPC7판) |
|
| 출원번호 | US-0111616 (1993-08-25) |
| 발명자 / 주소 |
|
| 출원인 / 주소 |
|
| 인용정보 | 피인용 횟수 : 282 인용 특허 : 0 |
A method and apparatus under software control for pattern recognition utilizes a neural network implementation to recognize two dimensional input images which are sufficiently similar to a database of previously stored two dimensional images. Images are first image processed and subjected to a Fouri
A method and apparatus under software control for pattern recognition utilizes a neural network implementation to recognize two dimensional input images which are sufficiently similar to a database of previously stored two dimensional images. Images are first image processed and subjected to a Fourier transform which yields a power spectrum. An in-class to out-of-class study is performed on a typical collection of images in order to determine the most discriminatory regions of the Fourier transform. A feature vector consisting of the highest order (most discriminatory) magnitude information from the power spectrum of the Fourier transform of the image is formed. Feature vectors are input to a neural network having preferably two hidden layers, input dimensionality of the number of elements in the feature vector and output dimensionality of the number of data elements stored in the database. Unique identifier numbers are preferably stored along with the feature vector. Application of a query feature vector to the neural network will result in an output vector. The output vector is subjected to statistical analysis to determine if a sufficiently high confidence level exists to indicate that a successful identification has been made. Where a successful identification has occurred, the unique identifier number may be displayed.
A pattern recognition system, comprising: first means for receiving a plurality of images and corresponding image identification information; second means for processing said plurality of images into image information; third means for determining the most distinctive aspects of said image informatio
A pattern recognition system, comprising: first means for receiving a plurality of images and corresponding image identification information; second means for processing said plurality of images into image information; third means for determining the most distinctive aspects of said image information, said third means including means for performing an In-Class to Out-of-Class study including: means for generating an In-Class Variation Matrix; means for generating an Out-Class Variation Matrix; means for normalizing said In-Class Variation Matrix; means for normalizing said Out-Class Variation Matrix; means for generating a feature Matrix; means for normalizing said feature Matrix into a normalized feature Matrix; means for partitioninq said normalized feature Matrix into bricks; means for prioritizing said bricks, and means for creating a feature template vector whose elements correspond to a subset of said bricks; fourth means for forming feature vectors of the magnitudes of said most distinctive aspects of said image information; fifth means for storing said feature vectors, said fifth means including neural network processor means adapted to store said feature vectors; sixth means for receiving a query image; seventh means for generating a query feature vector from said query image; eighth means for querying said fifth means to determine the most similar previously stored feature vectors to said query feature vector; ninth means for outputting image identification information corresponding to the previously stored feature vector most similar to said query feature vector.
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