Skin Color Registration Using Recognition of Waving Hands

2010 ◽  
Vol 22 (3) ◽  
pp. 262-272
Author(s):  
Kota Irie ◽  
◽  
Masahito Takahashi ◽  
Kenji Terabayashi ◽  
Hidetoshi Ogishima ◽  
...  
Keyword(s):  
Time Series ◽  
Individual Differences ◽  
Skin Color ◽  
Color Images ◽  
Color Information ◽  
Low Resolution ◽  
Hand Gestures ◽  
Lighting Conditions ◽  
Low Resolution Images

This paper proposes skin color registration using the recognition of waving hands. In order to recognize hand gestures from images, skin colors are useful information. The proposed method can register skin colors simply and quickly because it uses just a few waves of the hand. The method consists of 2 steps. First, the regions of the waving hands are extracted from low-resolution images without using color information. Second, the color values of the extracted regions are classified into background colors and hand colors depending on time series of color images. The color information classified as hand colors is registered as skin colors. The proposed method is robust against lighting conditions and individual differences in skin color, because the skin color is registered as an adapted skin color in each case. Several experiments are conducted to demonstrate the effectiveness of the proposed method.

Face Localization in Color Images Based on Skin Color and Eye Gradient

2011 ◽  
Vol 268-270 ◽  
pp. 1382-1385
Author(s):  
Yun Juan Liang ◽  
Xiao Ying Wu ◽  
Li Juan Ma ◽  
Li Jun Zhang
Keyword(s):  
Skin Color ◽  
Color Images ◽  
Color Model ◽  
Human Face ◽  
Color Information ◽  
Eye Localization ◽  
Illumination Changes ◽  
Skin Color Model ◽  
Candidate Regions ◽  
Face Localization

In color images, skin color is the important information on human face. This paper proposes a method to detect and locate human face rapidly based on skin color information and eye gradient. First, normalized RGB space is converted to HSV space; Secondly, the images are pretreated by smoothing and light compensation to overcome the uneven illumination changes, and then the defined skin color model is used to determine candidate regions of the human face, finally the human face is located accurately through eye localization based on gradient template. Experiments show that the method is fast and effective.

Caricaturing as a general method to improve poor face recognition: Evidence from low-resolution images, other-race faces, and older adults.

2019 ◽  
Vol 25 (2) ◽  
pp. 256-279 ◽  
Author(s):  
Amy Dawel ◽  
Tsz Ying Wong ◽  
Jodie McMorrow ◽  
Callin Ivanovici ◽  
Xuming He ◽  
...  
Keyword(s):  
Older Adults ◽  
Face Recognition ◽  
Low Resolution ◽  
General Method ◽  
Low Resolution Images

scholarly journals Modified Crack Detection of Sewer Conduit with Low-Resolution Images

2021 ◽  
Vol 11 (5) ◽  
pp. 2263
Author(s):  
Byung Jik Son ◽  
Taejun Cho
Keyword(s):  
Image Processing ◽  
Crack Detection ◽  
Threshold Value ◽  
Optimal Threshold ◽  
Optimal Parameters ◽  
Low Resolution ◽  
The Subject ◽  
Low Resolution Images

Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. Particularly, devices of less than 100,000 pixels are still widely used, and the environment for image processing is very dim. Since the sewage conduit images covered in this study have a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolutions of the sewer conduit images are very low in Korea, this problem of low resolution was selected as the subject of this study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Despite the very low resolution, the cracked images showed a 96.4% accuracy of detection, and the non-cracked images showed 94.5% accuracy. Moreover, the analysis was excellent in quality. It is believed that the findings of this study can be effectively used for crack detection with low-resolution images.

scholarly journals DMAS Beamforming with Complementary Subset Transmit for Ultrasound Coherence-Based Power Doppler Detection in Multi-Angle Plane-Wave Imaging

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4856
Author(s):  
Che-Chou Shen ◽  
Yen-Chen Chu
Keyword(s):  
Plane Wave ◽  
Power Doppler ◽  
P Value ◽  
Low Resolution ◽  
Ensemble Averaging ◽  
Stationary Tissue ◽  
Wave Imaging ◽  
Acquisition Delay ◽  
Complementary Subset ◽  
Low Resolution Images

Conventional ultrasonic coherent plane-wave (PW) compounding corresponds to Delay-and-Sum (DAS) beamforming of low-resolution images from distinct PW transmit angles. Nonetheless, the trade-off between the level of clutter artifacts and the number of PW transmit angle may compromise the image quality in ultrafast acquisition. Delay-Multiply-and-Sum (DMAS) beamforming in the dimension of PW transmit angle is capable of suppressing clutter interference and is readily compatible with the conventional method. In DMAS, a tunable p value is used to modulate the signal coherence estimated from the low-resolution images to produce the final high-resolution output and does not require huge memory allocation to record all the received channel data in multi-angle PW imaging. In this study, DMAS beamforming is used to construct a novel coherence-based power Doppler detection together with the complementary subset transmit (CST) technique to further reduce the noise level. For p = 2.0 as an example, simulation results indicate that the DMAS beamforming alone can improve the Doppler SNR by 8.2 dB compared to DAS counterpart. Another 6-dB increase in Doppler SNR can be further obtained when the CST technique is combined with DMAS beamforming with sufficient ensemble averaging. The CST technique can also be performed with DAS beamforming, though the improvement in Doppler SNR and CNR is relatively minor. Experimental results also agree with the simulations. Nonetheless, since the DMAS beamforming involves multiplicative operation, clutter filtering in the ensemble direction has to be performed on the low-resolution images before DMAS to remove the stationary tissue without coupling from the flow signal.

Face Image Segmentation Using Color Information and Saliency Map

2011 ◽  
Vol 55-57 ◽  
pp. 77-81
Author(s):  
Hui Ming Huang ◽  
He Sheng Liu ◽  
Guo Ping Liu
Keyword(s):  
Image Segmentation ◽  
Human Skin ◽  
Skin Color ◽  
Saliency Map ◽  
Face Image ◽  
Color Information ◽  
Attention Model ◽  
Face Area ◽  
Face Region ◽  
The Face

In this paper, we proposed an efficient method to address the problem of color face image segmentation that is based on color information and saliency map. This method consists of three stages. At first, skin colored regions is detected using a Bayesian model of the human skin color. Then, we get a chroma chart that shows likelihoods of skin colors. This chroma chart is further segmented into skin region that satisfy the homogeneity property of the human skin. The third stage, visual attention model are employed to localize the face region according to the saliency map while the bottom-up approach utilizes both the intensity and color features maps from the test image. Experimental evaluation on test shows that the proposed method is capable of segmenting the face area quite effectively，at the same time, our methods shows good performance for subjects in both simple and complex backgrounds, as well as varying illumination conditions and skin color variances.

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