Feature Extraction Algorithms to Color Image

Author(s):  
QingE Wu ◽  
Weidong Yang

The existing image processing algorithms mainly studied on feature extraction of gray image with one-dimensional parameter, such as edges, corners. However, the extraction of some characteristic points to color image with three-dimensional parameters, such as the extraction of color edge, corner points, inflection points, etc., is an image problem to be urgently solved. In order to carry out a fast and accurate feature extraction on color image, this paper proposes two types of extraction algorithms to color edge and corner points of color image, i.e., similar color segment algorithm and pixel probabilistic algorithm, compares with the two algorithms, gives the two algorithms are used to different color distribution situations, as well as shows the extraction effect of color by the combination of the two algorithms, moreover, gives the contrast experiment and effect analysis of the two algorithms. To compare the similar color segment algorithm with the probabilistic algorithm, experimental results show that the similar color segment algorithm is better than the pixel probabilistic algorithm under the more obvious color edge, because it has the better edge detection, stronger anti-noise ability, faster processing speed and other advantages. Under the transition phase of color edge is gentle or color edge is no clear, the image detection effect of the pixel probabilistic algorithm is better than that of the similar color segment algorithm. But the combinative effect of the two algorithms is the best in this case, which is more close to the color effect of original image. Moreover, this paper analyzes the performance of the similar color segment algorithm, and gives the comparison of the proposed two algorithms and existing classical algorithms used usually to feature extraction of color image. The two algorithms proposed and these researches development in this paper have not only enriched the contents of image processing algorithms, but also provide a solution tool for image segmentation, feature extraction to target, precise positioning, etc., such as extraction of complexion, physiological color photographs processing, feature extraction of ionosphere, detection and extraction of biological composition of oceans, to be applied to a lots of departments, such as the police, hospital departments, surgery, polar department, and so on, as well as provide a way of thinking for the rapid, accurate detection of case, surgery, scientific research information search.

2018 ◽  
pp. 397-420
Author(s):  
QingE Wu ◽  
Weidong Yang

The existing image processing algorithms mainly studied on feature extraction of gray image with one-dimensional parameter, such as edges, corners. However, the extraction of some characteristic points to color image with three-dimensional parameters, such as the extraction of color edge, corner points, inflection points, etc., is an image problem to be urgently solved. In order to carry out a fast and accurate feature extraction on color image, this paper proposes two types of extraction algorithms to color edge and corner points of color image, i.e., similar color segment algorithm and pixel probabilistic algorithm, compares with the two algorithms, gives the two algorithms are used to different color distribution situations, as well as shows the extraction effect of color by the combination of the two algorithms, moreover, gives the contrast experiment and effect analysis of the two algorithms. To compare the similar color segment algorithm with the probabilistic algorithm, experimental results show that the similar color segment algorithm is better than the pixel probabilistic algorithm under the more obvious color edge, because it has the better edge detection, stronger anti-noise ability, faster processing speed and other advantages. Under the transition phase of color edge is gentle or color edge is no clear, the image detection effect of the pixel probabilistic algorithm is better than that of the similar color segment algorithm. But the combinative effect of the two algorithms is the best in this case, which is more close to the color effect of original image. Moreover, this paper analyzes the performance of the similar color segment algorithm, and gives the comparison of the proposed two algorithms and existing classical algorithms used usually to feature extraction of color image. The two algorithms proposed and these researches development in this paper have not only enriched the contents of image processing algorithms, but also provide a solution tool for image segmentation, feature extraction to target, precise positioning, etc., such as extraction of complexion, physiological color photographs processing, feature extraction of ionosphere, detection and extraction of biological composition of oceans, to be applied to a lots of departments, such as the police, hospital departments, surgery, polar department, and so on, as well as provide a way of thinking for the rapid, accurate detection of case, surgery, scientific research information search.


2014 ◽  
Author(s):  
Jamison Whitesell ◽  
Dorin Patru ◽  
Eli Saber ◽  
Gene Roylance ◽  
Brad Larson

2013 ◽  
Vol 753-755 ◽  
pp. 2131-2134
Author(s):  
Da Wei Wu ◽  
Zhen Yu Xiong ◽  
Wang Ping Gu ◽  
Jun Shan

A molten pool image gathering system is designed based on multiple visions. By using a composite filter, it can effectively overcome the interference of the welding arc and obtain a clear molten pool image. A series of image processing algorithms has been proposed based on the features of the molten pool image. A median filtering has been used to remove the noise of the molten pool image. A canny multi-threshold method has been used to extract the edge characteristics of the molten pool. Then the edge feature of the molten pool can be gotten after false edge removing and iterative fitting.


Proceedings ◽  
2021 ◽  
Vol 63 (1) ◽  
pp. 72
Author(s):  
Razvan Cazacu

Image processing and the analysis of images in order to extract relevant data is an ever-growing topic of research. Although there are numerous methods readily available, the task of image preprocessing and feature extraction requires developing specific algorithms for specific problems by combining different functions and tweaking their parameters. This paper proposes a framework that allows the flexible construction of image processing algorithms. Its user interface and architecture are designed to ease and speed up the process of algorithm creation and testing as well as serve as an application for the use of these algorithms by end users. The framework was built in Matlab and makes use of its integrated Image Processing toolbox.


2018 ◽  
Vol 12 (12) ◽  
pp. 2153-2162 ◽  
Author(s):  
Sairamya Nanjappan Jothiraj ◽  
Thomas George Selvaraj ◽  
Balakrishnan Ramasamy ◽  
Narain Ponraj Deivendran ◽  
Subathra M.S.P

Author(s):  
César D. Fermin ◽  
Dale Martin

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.


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