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Feature extraction simplifies the amount of information needed to describe the properties of an image accurately. This paper measures the performance of a CBIR system based on texture feature against combination of both color and texture feature. A Gray Level Co-occurrence Matrix is calculated for computing the texture feature of an image. Using these textual parameters similar images are extracted...
the gray gradient co-occurrence matrix based Uyghur document image retrieval method is proposed in this paper. 15 parameters of gray gradient co-occurrence matrix such as small gradient advantage, high gradient strengths, intensity in homogeneity etc are extracted separately, and document image features are matched with the characteristic distance classifier and the Euclidean distance classifier....
An up-to-date comparison of state-of-the-art low-level color and texture feature extraction methods, for the purpose of content-based image retrieval (CBIR) is presented in this paper. The CBIR problem is motivated by the need to search the exponentially increasing space of image and video databases efficiently and effectively. We implement and compare color and texture feature extraction algorithms...
Palmprint Recognition Systems (PRS) with multi-feature can increase the recognition performance of PRS. For such a purpose, effectively distinguished information with low dimension is important in fusion for palmprint recognition. Usually, color information is a beneficial feature in image retrieval. But it is always ignored in recognition. This paper proposes a novel palmprint recognition algorithm...
This paper proposes a new simple method of Discrete Cosine Transform (DCT) feature extraction that is used to accelerate the speed and decrease the storage needed in the image retrieving process. Image features are accessed and extracted directly from JPEG compressed domain. This method extracts and constructs a feature vector of histogram quantization from partial DCT coefficient in order to count...
This paper describes a project that implements and tests a simple color histogram based search and retrieve algorithm for images. The study finds the technique to be effective as shown by analysis using the RankPower measurement. The testing also highlights the weaknesses and strengths of the model, concluding that the technique would have to be augmented and modified in order for practical use.
The paper presents a new approach for content based retrieval of images. The algorithm uses information sampled from around detected corner points in the image. A corner detection approach based on line intersections has been employed using Hough transform for line detection and then finding intersecting, near intersecting or complex shaped corners. As the affine transformations preserve the co-linearity...
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