Histogram-based template matching is an important method to search the globe optimization exhaustively. However, this method is commonly algorithmic complex. In this paper, we propose to replace the traditional histogram-based method with equivalent histogram-based method, which distinctly improves the matching efficiency. We first introduce the equivalent histogram on the basis of the relative...

As we know, histogram matching is a commonly-adopted technique in the applications of pattern recognition. The matching of two patterns can be accomplished by matching their corresponding histograms. In general, the number of features and the resolution of each feature will determine the size of histogram. The more the number of features and the higher the resolution of each feature, the strong...

In this paper, we propose a On-line kernel-PLS approach to improving both the robustness and accuracy of object tracking which is appropriate for real-time video surveillance. Typical tracking with color histogram matching provides robustness but has insufficient accuracy, because it does not involve spatial information. On the other hand, tracking with pixel-wise matching achieves accurate per...

Color based image retrieval is an important research area in digital image processing and Color is the useful property of the image. The challenging task is to find an efficient and accurate color images similar value and some limitations between two different types of image are matching such as compressed color image and RGB color image, RGB image and HSV color image, color image and 90 degree...

Scene matching is the process of recognizing two images as different views of the same scene captured using different sensor poses, and/or different types of sensors. In this work, each image contains the same objects and sensor pose parameters are not known. The spatial relationships among objects in the image, calculated using the histogram of forces (Fhistogram) method, are used as matching ...

In this paper we present a novel approach which is combined local invariant feature descriptor named ARPIH (Angular Radial Partitioning Intensity Histogram) with histogram-based similar distance (HSD). The approach succeeds the ARPIH descriptor’s distinctive advantage and provides higher robustness in deformation image matching, such as rotation image, illumination changing image and perspectiv...

Histogram search characterizes an image by its color distribution. It represents a popular mean of feature representation in computer vision. In This paper, we developed an efficient algorithm for image searching based on matching of Histogram using fuzzy sets. We used Fuzzy Sets in This paper for performing Image searching efficiently. We investigated histogram search methods in two different ...

A novel shape descriptor, named as ratio histograms (R-histogram), is proposed to represent the relative attitude relationship between two independent shapes. For a pair of two shapes, the shapes are treated as the longitudinal segments parallel to the line connecting centroids of the two shapes, and the R-histogram is composed of the length ratios of collinear longitudinal segments. R-histogra...

Radiometric normalization is critical for multi-spectral image change detection. In this paper, a histogram matching method is proposed to perform relative radiometric normalization among heterogeneously sensed images. To quantify the histogram matching quality, which is reference image and band dependent, the image differencing based quantitative measure, such as Euclidean or Manhattan distanc...