scholarly journals Anna May Wong and the Color Image

2021 ◽  
Vol 5 (2) ◽  
pp. 59-73
Author(s):  
Homay King

Abstract In Cinema 1, Deleuze proposes the “color-image,” a type of film image with an “absorbent characteristic” that does not refer to a particular object but seizes all that happens within its range. Like color-images, racial categories have an absorbent, seizing quality: they assert “color” at the expense of the object of representation. Deleuze does not address the potential applications of his concept to race, but they are especially illuminating when applied to early color-process cinema. This essay approaches The Toll of the Sea (dir. Chester M. Franklin, 1922), starring Anna May Wong and set in China, the first Technicolor film to be widely distributed in general release, as a feature-length “China Girl” and feature-length color-image, in Deleuze's sense. It further shows how Wong and her world are virtualized in this film under the rubric of a fictional orientalist palette.

Author(s):  
Gaber Hassan ◽  
Khalid M. Hosny ◽  
R. M. Farouk ◽  
Ahmed M. Alzohairy

One of the most often used techniques to represent color images is quaternion algebra. This study introduces the quaternion Krawtchouk moments, QKrMs, as a new set of moments to represent color images. Krawtchouk moments (KrMs) represent one type of discrete moments. QKrMs use traditional Krawtchouk moments of each color channel to describe color images. This new set of moments is defined by using orthogonal polynomials called the Krawtchouk polynomials. The stability against the translation, rotation, and scaling transformations for QKrMs is discussed. The performance of the proposed QKrMs is evaluated against other discrete quaternion moments for image reconstruction capability, toughness against various types of noise, invariance to similarity transformations, color face image recognition, and CPU elapsed times.


Author(s):  
Mohammadreza Hajiarbabi ◽  
Arvin Agah

Human skin detection is an important and challenging problem in computer vision. Skin detection can be used as the first phase in face detection when using color images. The differences in illumination and ranges of skin colors have made skin detection a challenging task. Gaussian model, rule based methods, and artificial neural networks are methods that have been used for human skin color detection. Deep learning methods are new techniques in learning that have shown improved classification power compared to neural networks. In this paper the authors use deep learning methods in order to enhance the capabilities of skin detection algorithms. Several experiments have been performed using auto encoders and different color spaces. The proposed technique is evaluated compare with other available methods in this domain using two color image databases. The results show that skin detection utilizing deep learning has better results compared to other methods such as rule-based, Gaussian model and feed forward neural network.


2018 ◽  
Vol 13 (3) ◽  
pp. 561-567
Author(s):  
Behzad Aliahmad ◽  
Aye Nyein Tint ◽  
Sridhar Poosapadi Arjunan ◽  
Priya Rani ◽  
Dinesh Kant Kumar ◽  
...  

Introduction: In clinical practice, both area and temperature of the ulcer have been shown to be effective in tracking the healing status of diabetes-related foot ulcer (DRFU). However, traditionally, the area of the DRFU is measured regardless of the temperature distribution. The current prospective, observational study used thermal imaging, as a more accurate tool, to measure both the area and the temperature of DRFU. We aimed to predict healing of DRFU using thermal imaging within the first 4 weeks of ulceration. Method: A pilot study was conducted where thermal and color images of 26 neuropathic DRFUs (11 healing vs 15 nonhealing) from individuals with type 1 or 2 diabetes were taken at the initial clinic visit (baseline), at week 2, and at week 4. The thermal images were segmented into isothermal patches to identify the wound boundary and area corresponding to temperature distribution. Five parameters were obtained: temperature of the wound bed, area of the isothermal patch of the wound bed, area of isothermal patch of periwound, number of isolated isothermal patches of the wound region, and physical wound bed area from color image. The ulcers were also measured by experienced podiatrists over 4 consecutive weeks and used as the healing reference. Results: For healing cases, the ratio of the area of the wound bed to its baseline measured using thermal images was found to be significantly lower at 2 weeks compared to nonhealing cases and this corresponded with a 50% reduction in area of DRFU at 4 weeks (group rank-based nonparametric analysis of variance P = .036). In comparison, neither the planimetric area measured using color images nor the temperature of the wound bed was associated with the healing. Conclusion: This study of 26 patients demonstrates that change in the isothermal area of DRFU can predict the healing status at week 4. Thermal imaging of DRFUs has the advantage of incorporating both area and temperature allowing for early prediction of the healing of these ulcers. Further studies with greater sample sizes are required to test the significance of these results.


2018 ◽  
Vol 2 (2) ◽  
pp. 63
Author(s):  
Ruaa Alaadeen Abdulsattar ◽  
Nada Hussein M. Ali

Error correction and error detection techniques are often used in wireless transmission systems. A color image of type BMP is considered as an application of developed lookup table algorithms to detect and correct errors in these images. Decimal Matrix Code (DMC) and Hamming code (HC) techniques were integrated to compose Hybrid Matrix Code (HMC) to maximize the error detection and correction. The results obtained from HMC still have some error not corrected because the redundant bits added by Hamming codes to the data are considered inadequate, and it is suitable when the error rate is low for detection and correction processes. Besides, a Hamming code could not detect large burst error period, in addition, the have same values sometimes which lead to not detect the error and consequently increase the error ratio. The proposed algorithm LUT_CORR is presented to detect and correct errors in color images over noisy channels, the proposed algorithm depends on the parallel Cyclic Redundancy Code (CRC) method that's based on two algorithms: Sarwate and slicing By N algorithms. The LUT-CORR and the aforementioned algorithms were merged to correct errors in color images, the output results correct the corrupted images with a 100 % ratio almost. The above high correction ratio due to some unique values that the LUT-CORR algorithm have. The HMC and the proposed algorithm applied to different BMP images, the obtained results from LUT-CORR are compared to HMC for both Mean Square Error (MSE) and correction ratio.  The outcome from the proposed algorithm shows a good performance and has a high correction ratio to retrieve the source BMP image.


2015 ◽  
Vol 743 ◽  
pp. 379-384 ◽  
Author(s):  
Zhang Li Lan ◽  
Lin Zhu ◽  
Yi Cai Li ◽  
Jun Liu

Key space will be reduced after using the traditional DES algorithm to directly encrypt color images. Through combining the chaotic capability of the logistic function and by means of a specific algorithm, the fake chaotic son key’s space which is produced by the logistic chaotic pseudo-random function could be acquired. Then use the key generation algorithm to replace the traditional DES key generation algorithm. Experiment illustrates that the proposed algorithm has stronger robustness and anti-jamming capability to noise, and larger key’s space, sensitive initial keys, and better encryption effect, meanwhile it is better immune to multiple attacks.


2019 ◽  
Vol 11 (4) ◽  
pp. 28-49 ◽  
Author(s):  
Mengmeng Zhang ◽  
Rongrong Ni ◽  
Yao Zhao

A blind print-recapture robust watermark scheme is proposed. Watermark patterns are embedded into the space domain of a color image and can be detected from a print-recaptured version of the image without knowledge of the original image. The process of embedding invisible watermarks to convert RGB color images to CIE Lab color spaces and embed periodic watermarks in both color channels at the same time. Watermark extraction is achieved by calculating self-convolution and inverting the geometric transformation such as rotation and scale. Normalized correlation coefficients between the extracted and the embedded watermark pattern is calculated to determine whether there is watermark. The decision about the presence/absence of the watermark pattern is then determined by a threshold which is set 0.13, and the detection rate of 241 pictures is about 0.79.


2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Hai Nan ◽  
Bin Fang ◽  
Weibin Yang ◽  
Jiye Qian ◽  
Ming Li ◽  
...  

With more color images being widely used on the Internet, the research on embedding color watermark image into color host image has been receiving more attention. Recently, Su et al. have proposed a robust and blind watermarking scheme for dual color image, in which the main innovation is the using of two-level DCT. However, it has been demonstrated in this paper that the original scheme in Su’s study is not secure and can be attacked by our proposed method. In addition, some errors in the original scheme have been pointed out. Also, an improvement measure is presented to enhance the security of the original watermarking scheme. The proposed method has been confirmed by both theoretical analysis and experimental results.


2010 ◽  
Vol 26-28 ◽  
pp. 48-54
Author(s):  
Jin Ling Wei ◽  
Jun Meng ◽  
Wei Song

According to the analysis of every feature element’s grey images in RGB color space and HSI color space, each of the elements represents different information of the color image. From the analysis of the Histogram of color images, the value range of hue H basically keeps stable, which is proved by experiments to be the most stable and representative one. Finally we illustrated by application instances that the method of recognition and tracking of the objective moving robot based on hue character H is applicable.


2014 ◽  
Vol 511-512 ◽  
pp. 550-553 ◽  
Author(s):  
Jian Yong Liang

Edge detection is an old and hot topic in image processing, pattern recognition and computer vision. Numerous edge detection approaches have been proposed to gray images. It is difficult to extend these approaches to color image edge detection. A novel edge detection method based on mathematical morphology for color images is proposed in this paper. The proposed approach firstly compute vector gradient based on morphological gradient operators, and then compute the optimal gradient according to structure elements with different size. Finally, we use a threshold to binary the gradient images and then obtain the edge images. Experimental results show that the proposed approach has advantages of suppressing noise and preserving edge details and it is not sensitive to noise pixel. The finally edge images via the proposed method have high PSNR and NC compared with the traditional approaches.


2011 ◽  
Vol 474-476 ◽  
pp. 2140-2145
Author(s):  
Si Li ◽  
Hong E Ren

Combined with the composition characteristics of forest fire image background when the forest fire occurred during different time periods of night and day, different image segmentation methods were applied to the forest fire color images of different time periods respectively, which could improve the efficiency of image processing. Meanwhile, application of H and S components from HSV color space, the strategy on color image segmentation which processed the segmentation processing to forest fire color images with complicated background was proposed combined with Otsu algorithm. The results of simulation experiment showed that the above-mentioned segmentation methods were obtained satisfactory segmentation effects when the segmentation on forest fire color images during different time periods of night and day were processed respectively. And also application of Otsu algorithm based on HSV color model, the forest fire image segmentation occurred in the daytime was processed, which overcame the interference factors of light and smoke, as well as the shortage of noise sensibility due to Otsu algorithm.


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