In this paper, we propose a new method for the detection and the recognition of objects in color images. The developed method processes in two steps. The first one concerns the object detection by a color segmentation method and a labeling algorithm. The second step deals with the recognition of extracted objects. Each object is described by color Zernike moments. In order to recognize each obj...

This paper presents a new moment-preserving thresholding technique, called the binary quaternion-moment-preserving (BQMP) thresholding, for color image data. Based on representing color data by the quaternions, the statistical parameters of color data can be expressed through the definition of quaternion moments. Analytical formulas of the BQMP thresholding can thus be determined by using the a...

Due to the large amounts of multimedia data prevalent on the Web, Some images presents textural motifs while others may be recognized with colors or shapes of their content. The use of descriptors based on one’s features extraction method, such as color or texture or shape, for automatic image annotation are not efficient in some situations or in absence of the chosen type. The proposed approac...

This paper contributes to the viewpoint and illumination independent recognition of planar color patterns such as labels, logos, signs, pictograms, etc. by means of moment invariants. It introduces the idea of using powers of the intensities in the different color bands of a color image and combinations thereof for the construction of the moments. First, a complete classification is made of all...

In this work we compare two spatial and two wavelet-domain feature extraction methods that have been proposed in the recent literature for color-texture classification. The corresponding color-texture features, namely the Opponent-Color Local Binary Pattern distributions, the Chromaticity Moments, the Wavelet Correlation Signatures and the Color Wavelet Covariance features, are extracted in RGB...

Content based image retrieval (CBIR) from large resources has become a dominant research field and found wide interest nowadays in many applications. In this thesis work, we design and implement a content based image retrieval system that uses color and texture as visual features to describe the content of an image region. We use k-nearest neighbor (knn) and HSV color model to extract feature o...

This dissertation reports on research, development, and evaluation of a color based video sequence identification and tracking algorithm. We describe an automatic video sequence identification and tracking algorithm that detects and extracts repeated video sequences from a continuous video stream. Because our technique is domain and video source independent, it is applicable to any video stream...

A hybrid approach based on Fuzzy Logic and neural networks with the combination of the classic Hu & Zernike moments joined with Geodesic descriptors is used to keep the maximum amount of information that are given by the color of the image. These moments are calculated for each color level and geodesic descriptors are applied directly to binary images to get information about the general shape ...