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| Titel: |
Principal Component Analysis Based Image Recognition |
| Auteur: |
ASHOK.J DR.E.G.RAJAN |
| Verschenen in: |
International journal of computer science and information technologies |
| Paginering: | Jaargang 1 (2010) nr. 2 pagina's 44-50 |
| Jaar: |
2010 |
| Inhoud: |
The aim of this paper is to recognize a query image from a database of images. This process involves finding the principal component of the image, which distinguishes it from the other images. PrincipalComponent Analysis (PCA) is a classical statistical method and is widely used in data analysis. The main use of PCA is to reduce the dimensionality of a data set while retaining as much information as possible. This paper uses the concept of PCA to recognize images byextracting their principal components. In this I have used 32X32, 24 bit gray scale bitmap images. For extraction of image attributes, the data file is extracted from the bitmap image file format. Discrete Cosine Transform is used to reduce the size of the data set so that the most relevant intensity information of the query image iscontained in a first few lower order frequency components. PCA is used to extract the unique characteristic of the query image, which distinguishes it from the other images. Hence comparison of the queryimage with the database of images will result in an exact match. |
| Uitgever: |
TechScience Publications (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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