• Corpus ID: 14422738

CBIR using Upper Six FFT Sectors of Color Images for Feature Vector Generation

  title={CBIR using Upper Six FFT Sectors of Color Images for Feature Vector Generation},
  author={H. B. Kekre and Dhirendra Mishra},
In this paper we are using Fast Fourier Transform to generate the feature vector which considers the mean real and mean imaginary parts of complex numbers of polar coordinates in frequency domain. The method proposed here considers 12 mean values of 6 upper half sectors real and imaginary parts of each R, G and B components of an image. The algorithm proposed uses 36 mean values of real and imaginary parts in total. The proposed work experimented over a database of 249 images spread across 10… 
Performance Comparison of Four , Eight & Twelve Walsh Transform Sectors Feature Vectors for Image Retrieval from Image Databases
This paper presents the idea of using Walsh transform to generate the feature vector for content based image retrieval This paper compares the performance of 4, 8 and 12 sectors of Walsh Transform.
DCT Sectorization for Feature Vector Generation in CBIR
This paper has introduced the new performance evaluation parameters i.e. LIRS and LSRR apart from precision and Recall, the traditional methods and proposed two different approaches along with augmentation of mean ofzero and highest row components of row transformed values in row wise DCT transformed image and mean of zero- and highest column components of Column transformedvalues in column wise D CT transformed image for feature vector generation.
Density Distribution in Walsh Transform Sectors as Feature Vectors for Image Retrieval
The density distribution of real and imaginary values of Walsh sectors in all three color planes are considered to design the feature vector and the algorithm proposed here is worked over database of 270 images spread over 11 different classes.
Performance Comparison of Density Distribution and Sector mean of sal and cal functions in Walsh Transform Sectors as Feature Vectors for Image Retrieval
In this paper we have proposed two different approaches for feature vector generation with absolute difference as similarity measuring parameter. Sal-cal vectors density distribution and Individual
CBIR Using DCT for Feature Vector Generation
The focus of this work is on using transformation technique for searching, browsing and retrieving images from a large database. In this paper we are using Discrete Cosine Transform to generate the
Comparison of CBIR Techniques using DCT and FFT for Feature Vector Generation
In innovative content based image retrieval (CBIR) techniques based on feature vectors as DC coefficients of transformed images using DCT and FFT, FFT surpasses DCT transforms in performance with highest precision and recall values.
DCT-DST Plane sectorization of Row wise Transformed color Images in CBIR
We have introduced a novel idea of sectoring of DCT-DST plane of Row wise transformed images and feature vector generation with and without augmentation of zeroth column component of DCT transformed
Column wise DCT plane sectorization in CBIR
Content Based Image Retrieval (CBIR) is the application of computer vision techniques used to retrieve digital images from a large database. In this paper we have used the concept of sectorization of
Content Based Image Retrieval using Density Distribution and Mean of Binary Patterns of Walsh Transformed Color Images
This paper introduces a novel idea of Binary Pattern observation of column wise and Row wise Walsh transformed color images for feature vector generation. The density distribution of Sal, Cal
Sectorization of DCT-DST Plane for Column Wise Transformed Color Images in CBIR
We have introduced a novel idea of sectorization of DCT-DST plane of column wise transformed color images and feature vector generation with and without augmentation of extra row components. We have


novel technique for image retrieval using the color- texture features extracted from images based on vector quantization with Kekre's fast codebook generation is proposed. This gives better
Boosting Block Truncation Coding with Kekre ’ s LUV Color Space for Image Retrieval
Information and Communication Technology (ICT), have increased the interest of people in the potential of images to store and share the information. The number of image achieves are growing with the
Image retrieval using augmented block truncation coding techniques
The new proposed methods are tested on the 1000 images database and the results show that the precession is improved in BTC- RGB and is even better in Spatial BTC-RGB.
Fingerprint matching using minutiae and texture features
A hybrid matching algorithm is presented that uses both minutiae (point) information and texture (region) information for matching the fingerprints and shows that a combination of the texture-based andMinutiae-based matching scores leads to a substantial improvement in the overall matching performance.
An efficient algorithm for the extraction of a Euclidean skeleton
  • Wai-Pak Choi, K. Lam, W. Siu
  • Computer Science, Mathematics
    2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 2002
A connectivity criterion that can be used to determine whether a given pixel inside an object is a skeleton point is proposed, based on a set of points along the object boundary, which are the nearest contour points to the pixel under consideration and its 8 neighbors.
Content-based image retrieval systems: A survey
In this paper, some technical aspects of current content-based image retrieval systems are surveyed.
Image database systems: A survey
The essential problems in IDB design are pointed out rather than classify the existing or proposed systems into an unestablished framework.
Shape description using weighted symmetric axis features
An application of symmetric axis geometry to shape classification and description, in which a sequential string of features is derived, and a weighting measure is developed which evaluates the importance of these shape descriptors.
Computing Voronoi diagrams in digital pictures
The 4-metric is adopted to construct the Voronoi diagram of a binary digital picture, whose foreground consists of arbitrarily shaped components and the various tiles are identified by using a component labeling technique.
Content-Based Image Retrieval Systems
In this paper we present image data representation, similarity image retrieval, the architecture of a generic content-based image retrieval system, and different content-based image retrieval