In this paper, we proposed a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of ...

This paper has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is fnished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture ...

Content-Based Image Retrieval (CBIR) systems have been widely used for a wide range of applications such as Art collections, Crime prevention and Intellectual property. In this paper, a novel CBIR system, which utilizes visual contents (color, texture and shape) of an image to retrieve images, is proposed. The proposed system builds three feature vectors and stores them into MySQL database. The...

with the increase of the number of cameras installed across a video surveillance network, the ability of security staffs to attentively scan all the video feeds actually decreases. therefore, the need for an intelligent system that operates as a tracking system is vital for security personnel to do their jobs well. tracking people as they move through a camera network with non-overlapping field...

The novel technique for image retrieval using the colortexture features extracted from images based on vector quantization with Kekre’s fast codebook generation is proposed. This gives better discrimination capability for Content Based Image Retrieval (CBIR). Here the database image is divided into 2x2 pixel windows to obtain 12 color descriptors per window (Red, Green and Blue per pixel) to fo...

Methods for machine learning (support vector machines) and image processing (color deconvolution) are combined in this paper for the purpose of separating colors in images of documents. After determining the background color, samples from the image that are representative of the colors to be separated are mapped to a feature space. Given the clusters of samples of either color the support vecto...

Content-based image retrieval (CBIR) systemwith relevance feedback, which uses the algorithm for feature-vector (FV) dimension reduction, is described. Feature-vector reduction (FVR) exploits the clustering of FV components for a given query. Clustering is based on the comparison of magnitudes of FV components of a query. Instead of all FV components describing color, line directions, and textu...