The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-bas...
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The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-based authentication systems. This paper presents a low-cost approach for automatic detection and characterization of human veins from IR images. The proposed method uses image processing techniques including segmentation, feature extraction, and, pattern recognition algorithms. Initially, the IR images are preprocessed to enhance vein structures and reduce noise. Subsequently, a clahe algorithm is employed to extract vein regions based on their unique IR absorption properties. Features such as vein thickness, orientation, and branching patterns are extracted using mathematical morphology and directional filters. Finally, a classification framework is implemented to categorize veins and distinguish them from surrounding tissues or artifacts. A setup based on Raspberry Pi was used. Experimental results of IR images demonstrate the effectiveness and robustness of the proposed approach in accurately detecting and characterizing human. The developed system shows promising for integration into applications requiring reliable and secure identification based on vein patterns. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.
This paper present a fast and simple medical image enhancing method based on locally redistributed histograms,which can enhance the contrast ratio of medical images *** with conventional enhancing methods,it can proce...
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This paper present a fast and simple medical image enhancing method based on locally redistributed histograms,which can enhance the contrast ratio of medical images *** with conventional enhancing methods,it can process images more clearly and suppress noise more efficiently,especially for medical images.
In the archives security system, light is an important factor of image definition, has a great influence on the subsequent processing and final regulation. In this paper, aiming at the gloomy weather and night low con...
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In the archives security system, light is an important factor of image definition, has a great influence on the subsequent processing and final regulation. In this paper, aiming at the gloomy weather and night low contrast image by using histogram equalization(HE), the adaptive histogram equalization(AHE) and contrast limited adaptive histogram equalization(clahe) algorithm for image processing and comparison, this paper presents an improved algorithm of contrast limited adaptive histogram equalization based on. Firstly, the RGB and YCbCr color space conversion. Second only to the luminance component of the contrast limited adaptive histogram equalization transformation and nonlinear tension change. Finally, the output image RGB. The experimental results show that, this method not only improves the contrast of the image, and in the monitoring of archives security system in good to keep the image information, and improve the effectiveness of subsequent recognition and monitoring.
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