Fingerprint compression based on sparse representation
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The document introduces a novel fingerprint compression algorithm based on sparse representation, showing its efficiency compared to existing methods like JPEG and WSQ at high compression ratios. It discusses the importance of biometric recognition, particularly fingerprints, and the challenges associated with the large data volumes from stored fingerprint images, emphasizing the need for effective compression techniques. The proposed solution utilizes a method of sparse representation for better compression while requiring standard hardware and software specifications.
Fingerprint compression based on sparse representation
- 1. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts FINGERPRINT COMPRESSION BASED ON SPARSE REPRESENTATION ABSTRACT A new fingerprint compression algorithm based on sparse representation is introduced. Obtaining an over complete dictionary from a set of fingerprint patches allows us to represent them as a sparse linear combination of dictionary atoms. In the algorithm, we first construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l0-minimization and then quantize and encode the representation. In this paper, we consider the effect of various factors on compression results. Three groups of fingerprint images are tested. The experiments demonstrate that our algorithm is efficient compared with several competing compression techniques (JPEG, JPEG 2000, and WSQ), especially at high compression ratios.
- 2. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts SCOPE OF WORK Recognition of persons by means of biometric characteristics is an important technology in the society, because biometric identifiers can’t be shared and they intrinsically represent the individual’s bodily identity. Among many biometric recognition technologies, fingerprint recognition is very popular for personal identification due to the uniqueness, universality, collectability and invariance. Large volumes of fingerprint are collected and stored every day in a wide range of applications, including forensics and access control. PROBLEM DEFINITION In 1995, the size of the FBI fingerprint card archive contained over 200 million items and archive size was increasing at the rate of 30 000 to 50 000 new cards per day. Large volume of data consume the amount of memory. Fingerprint image compression is a key technique to solve the problem. PROPOSED SOLUTION Compression technologies can be classed into lossless and lossy. Lossless compression allows the exact original images to be reconstructed from the
- 3. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts compressed data. Lossless compression technologies are used in cases where it is important that the original and the decompressed data are identical. Avoiding distortion limits their compression efficiency. When used in image compression where slight distortion is acceptable, lossless compression technologies are often employed in the output coefficients of lossy compression. Lossy compression technologies usually transform an image into another domain, quantize and encode its coefficients. EXISTING SYSTEM Compression technologies can be classed Lossless and Lossy Lossless compression This allows the exact original images to be reconstructed from the compressed data. Lossy compression Transform an image into another domain, quantize and encode its coefficients. Transform-based image compression technologies
- 4. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts Transform-based image compression technologies have been extensively researched and some standards have appeared. Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) Discrete Cosine Transform The DCT-based encoder can be thought of as compression of a stream of 8 × 8 small block of images. This transform has been adopted in JPEG. The JPEG compression scheme has many advantages such as simplicity, universality and availability. Disadvantages However, it has a bad performance at low bit-rates mainly because of the underlying block-based DCT scheme. Discrete Wavelet Transform The DWT-based algorithms include three steps: a DWT computation of the normalized image, quantization of the DWT coefficients and lossless coding of the quantized coefficients. There are several other DWT-based algorithms, such as Set Partitioning in Hierarchical Trees (SPIHT) Algorithm. These algorithms are for general image compression.
- 5. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts Wavelet Scalar Quantization Targeted at fingerprint images, these are special algorithms Wavelet Scalar Quantization (WSQ). It became the FBI standard for the compression of 500 dpi fingerprint images. There are other algorithms for fingerprint compression, such as Contourlet Transform (CT). These algorithms have a common shortcoming, namely, without the ability of learning. The fingerprint images can’t be compressed well now. They will not be compressed well later. Disadvantages DCT has a bad performance at low bit-rates mainly because of the underlying block-based DCT scheme. PROPOSED SYSTEM A novel approach based on sparse representation is proposed. To construct a base matrix whose columns represent features of the fingerprint images, referring the matrix dictionary whose columns are called atoms For a given whole fingerprint, divide it into small blocks called patches whose number of pixels are equal to the dimension of the atoms
- 6. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts To use the method of sparse representation to obtain the coefficients; then, quantize the coefficients; last, encode the coefficients and other related information using lossless coding methods. Advantages Good compression ration Lossless image compression is achieved Hardware requirements: Processor : Any Processor above 500 MHz. Ram : 128Mb. Hard Disk : 10 Gb. Compact Disk : 650 Mb. Input device : Standard Keyboard and Mouse. Output device : VGA and High Resolution Monitor. Software requirements: Operating System : Windows Family. Language : JDK 1.5