A comparison of hardware/software techniques in the speedup of color image processing algorithms

2014 ◽  
Author(s):  
James Mazza ◽  
Dorin Patru ◽  
Eli Saber ◽  
Gene Roylance ◽  
Brad Larson
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Color Image Processing ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Design for implementation of color image processing algorithms

2014 ◽  
Author(s):  
Jamison Whitesell ◽  
Dorin Patru ◽  
Eli Saber ◽  
Gene Roylance ◽  
Brad Larson
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Color Image Processing ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Feature Extraction Algorithms to Color Image

2017 ◽  
pp. 27-50
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Color Image ◽  
Probabilistic Algorithm ◽  
Corner Points ◽  
Case Surgery ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Different Color ◽  
Better Than

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.

Evaluation of apple flowering intensity using color image processing for tree specific chemical thinning

2017 ◽  
Vol 8 (2) ◽  
pp. 466-470
Author(s):  
O. Krikeb ◽  
V. Alchanatis ◽  
O. Crane ◽  
A. Naor
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Apple Orchard ◽  
Color Image Processing ◽  
Specific Chemical ◽  
Growing Seasons ◽  
Automatic Estimation ◽  
Image Processing Algorithms ◽  
Individual Trees ◽  
Flowering Intensity

Chemical thinning in apple orchards is a commonly used technique for improving yield. The objective of this work was to quantify bloom intensity of individual trees using color images, and estimate the time for the peak of the bloom. Image acquisition campaigns were conducted in an apple orchard with Golden Delicious variety during two growing seasons. Image processing algorithms were developed to detect flowers. The correlation between the manual and automatic estimation of bloom intensity at the day of the peak was 0.90 and 0.97 for 2014 and 2015 respectively. Based on the above relationships, maps of blooming intensity were derived and its variability was established.

Feature Extraction Algorithms to Color Image

2018 ◽  
pp. 397-420
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Color Image ◽  
Probabilistic Algorithm ◽  
Corner Points ◽  
Case Surgery ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Different Color ◽  
Better Than

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.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

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.

Elastic Graph-based Semi-supervised Embedding with Adaptive Loss Regression

2020 ◽  
Keyword(s):  
Image Processing ◽  
International Symposium ◽  
Fast Track ◽  
Electronic Imaging ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Image Processing: Algorithms and Systems proceedings.

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