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Image and video sensors are increasingly being deployed in complex systems due to the rich process information that these sensors can capture. As a result, image data play an important role in process monitoring and control in different application domains such as manufacturing processes, food industries, medical decision-making, and structural health monitoring. Existing process monitoring techniques...
In different color spaces, the three color channels might have different relationship, but most of color face recognition methods exploit the color information in a simple way. In this paper, we propose a novel hybrid fusion scheme for color face recognition, which first uses two-phase test sample representation (TPTSR) to obtain matching scores of each color channel of the test sample and then uses...
To solve the problem of accuracy and robustness seriously affected by the external environment when loop-closing using vision for mobile robot, a method based on RGB-D image for loop-closing detection is proposed. The front area contour which will be used for contour matching is extracted from the depth information. Then Image matching between similar scenes of candidates is done Using PCA-SIFT descriptors,...
Colorization is an appealing area in the world of image processing. It has been used to increase the visual appeal of images such as old black and white photos, classic movies or scientific illustrations. Also, It has been very important in color image compression and video compression. Colorization, the task of coloring a grayscale image or video, involves assigning an intensity or luminance from...
This paper introduces several novel color, shape and texture-based image descriptors for scene image classification with applications to image search and retrieval. Specifically, first, a new 3-Dimensional Local Binary Pattern (3DLBP) descriptor is proposed for color image local feature extraction. Second, a new shape descriptor (HaarHOG) is introduced by combining Haar wavelet transformation and...
This paper proposes a feature extraction approach inspired by the Scale Invariant Feature Transform (SIFT) algorithm. We compute the color gradient based on Principal Component Analysis (PCA). To discover the correct keypoints position, we use the hue information of the image and apply our own color corner detection algorithm, described further in this article. We present our results, both on images...
The goal of image segmentation in imaging science is to solve the problem of partitioning an image into smaller disjoint homogeneous regions that share similar attributes. The novel technique of the expectation-maximization (EM) algorithm based on principal component analysis (PCA) with adaptively selecting dominant factors for color image segmentation in color spaces is studied here. And simultaneously,...
Mean shift is an efficient filtering algorithm processing multidimensional data as color images. Such algorithm needs few tuning parameters named scale parameters. In this paper, we study the impact of the color space used on the results quality. Two linear transformations of the RGB space (Y'UV and PC A) and a non linear one (L∗a∗b∗ color space) are addressed. The results quality is assessed using...
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