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An algorithm combining both gray level information and geometric features is introduced to detect cast shadows in gray level images. A simply connected candidate shadow region and a corresponding region are segmented by setting gray level thresholds, and neighbor-matching regions are constructed with mathematical morphological algorithm. Shadow-non-shadow region pair is obtained from the result of...
This paper presents a fast and accurate object search algorithm based on template matching. Template matching is an important technique within the field of image processing for searching object region from images which matches a template. Template matching has a problem that existence of background in a template causes search error. To avoid such error, in the proposed object search, a procedure called...
Aims to provide general technicians who manage pects in production with a convenient way to recognize them, a novel method to classify insects by analyzing color histogram and GLCM (Gray-Level Co-occurrence Matrices) of wing images is proposed. The wing image of lepidopteran insect is preprocessed to get the ROI (Region of Interest); then the color image is first converted from RGB(Red-Green-Blue)...
The paper presents a new tracking scheme based on the object-strips color (OSC) feature. Firstly, the images captured by the camera are transformed into a format which is suitable for object tracking. Secondly, background subtraction method is used to detect the moving object. Then the OSC feature is represented by dividing the detected object into several strips and integrating the mean hue of each...
In order to make the fingerprint image pre-processing algorithm be more consistent with human visual cognitive processes, we accorded to visual perception model to calculate visual experience gray value, and calculate the parameters of the fingerprint image segmentation, achieved a new method. First, the fingerprint image is segmented using the method called OSTU with the physical gray value; Second,...
Content-based image retrieval relies on the use of efficient and effective image descriptors. One of the most important components of an image descriptor is concerned with the distance function used to measure how similar two images are. This paper presents a clustering approach based on distances correlation for computing the similarity among images. Conducted experiments involving shape, color,...
Recently, local stereo matching has experienced large progress by the introduction of adaptive support-weights. In this paper, we aim at eliminating negative effects of occlusions by proposing an occlusion-based method to improve traditional support weights. Weights of occluded points are greatly reduced while computing matching costs, initial disparities and final disparities. Experimental results...
This study introduces a novel classification algorithm for learning and matching sequences in view independent object tracking. The proposed learning method uses adaptive boosting and classification trees on a wide collection (shape, pose, color, texture, etc.) of image features that constitute a model for tracked objects. The temporal dimension is taken into account by using k-mean clusters of sequence...
In this paper, we present the fusional feature composed of Affine-SIFT, MSER and color moment invariants. The fusional feature is more robust and distinctive than a single local feature. Instead of adding three local features together simply, an efficient two-level matching strategy is devised with the fusional feature, which speeds up the establishment of the local correspondences. To remove partial...
Most iris recognition systems use the global and local texture information of the iris in order to recognize individuals. In this work, we investigate the use of macro-features that are visible on the anterior surface of RGB images of the iris for matching and retrieval. These macro-features correspond to structures such as moles, freckles, nevi, melanoma, etc. and may not be present in all iris images...
We propose in this paper to study different color spaces for representing an image for the face authentication application. We used a generic algorithm based on a matching of keypoints using sift descriptors computed on one color component. Ten color spaces have been studied on four large and significant benchmark databases (ENSIB, FACES94, AR and FERET). We show that all color spaces do not provide...
This paper deals with feature matching and segmentation of common objects in a pair of images, simultaneously. For the feature matching problem, the matching likelihoods of all feature correspondences are obtained by combining their discriminative power with the spatial coherence constraint that favors their spatial aggregation via object segmentation. At the same time, for the object segmentation...
We investigate several topics related to manifold-techniques for signal processing. On the most general level we consider manifolds with a Riemannian Geometry. These manifolds are characterized by their inner products on the tangent spaces. We describe the connection between the symmetric positive-definite matrices defining these inner products and the Cartan and the Iwasawa decomposition of the general...
Two algorithms are proposed in this article to improve the matching of stereo image pairs. One is the improved algorithm of adaptive image window; the other is an improved algorithm in edge pixel areas, which is used to enhance the correction rate of matching the edge pixels by reducing the Corr (color correlation measurement) of the edge pixels. These two algorithms are investigated by matching four...
In this paper, we propose a hybrid approach for addressing feature-based matching problem. We aim to obtain robust and accurate correspondence between features from image frames under unknown and unstructured environments. The approach incorporates image texture analysis, 2-D analytic signal theory and color modeling. It takes advantage of geometric invariant property in texture and monogenic signal...
We propose a framework to combine geometry, color and texture information among pairwise feature points into a graph and find the correct assignments from all candidates using graph matching techniques. Because of our informative similarity matrix, objects can be still recognized under severe occlusion and the matching errors can be greatly reduced when images are taken from very different view angles...
In this paper, we present a new solution to the problem of matching groups of people across multiple non-overlapping cameras. Similar to the problem of matching individuals across cameras, matching groups of people also faces challenges such as variations of illumination conditions, poses and camera parameters. Moreover, people often swap their positions while walking in a group. In this paper, we...
This paper proposes an image classification method based on extracting image features using Haar random forests and combining them with a spatial matching kernel SVM. The method works by combining multiple efficient, yet powerful, learning algorithms at every stage of the recognition process. On the task of identifying aquatic stonefly larvae, the method has state-of-the-art or better performance,...
Digital image forensics seeks to detect statistical traces left by image acquisition or post-processing in order to establish an images source and authenticity. Digital cameras acquire an image with one sensor overlayed with a color filter array (CFA), capturing at each spatial location one sample from the three necessary color channels. The missing pixels must be interpolated in a process known as...
In this paper a new filtering framework for colour image sequences corrupted by random impulse noise is introduced. The proposed method consists of three successive filtering steps in order to find a good trade-off between detail preservation and noise removal. One hard filtering step, that should remove all the noise at once, would namely also remove a considerable amount of details. In the different...
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