A sign language image segmentation method based on centroid positioning and distance transformation

Abstract

The invention discloses a sign language image segmentation method based on centroid positioning and distance transformation. The method comprises the following steps: firstly, converting a read sign language image into a YCbCr color space, and performing skin color clustering; Performing smoothing processing on the segmented sign language image by adopting median filtering, performing maximum threshold binaryzation on the filtered sign language image, and finally performing processing by adopting an image region filling algorithm to ensure the integrity of a sign language region in the image;performing Processing by adopting area operator and centroid positioning to obtain a hand-arm region; separating the hand-arm region by the distance-based image based on the distance transform method,so as to achieve accurate segmentation of the hand region and the arm region. The method provided by the invention solves the problem of segmentation of the arm area, is suitable for segmentation oftwo conditions of a large bent arm and a long arm, has good robustness, can adapt to the two arm conditions, and can also adapt to gesture rotation and gesture size change.

Description

technical field [0001] The invention relates to an image segmentation method, in particular to a sign language image segmentation method based on centroid location and distance transformation. Background technique [0002] Gesture segmentation is a key step in the process of gesture recognition, and ensuring a good segmentation effect is an important condition for accurate recognition of sign language. How to accurately segment gestures from complex backgrounds is always a difficult point, mainly because the gesture environment is easily affected by factors such as lighting. Currently common gesture segmentation techniques include segmentation based on contour information, segmentation based on skin color information, and segmentation based on motion information. [0003] Segmentation based on contour information is to extract the smooth and continuous contour of the target object from the image. Color-based segmentation is based on whether the specified area has skin colo...

AI Technical Summary

Problems solved by technology

[0004] There are many methods of gesture segmentation, but in the actual segmentation process, it is difficult for a single method to meet the requirements of speed, accuracy and fitness at the same time. In practical applications, multi-method joint segmentation is usually combined with the advantages of various algorithms in the application scene

The main challenges of current gesture segmentation are as follows: 1) Gesture is a non-rigid object with various contours and sizes, and it is difficult to obtain the contour information of gestures; 2) The skin-like area in the gesture image will affect the gesture The results of the segmentation are affected; 3) The redundant information of the arm part is difficult to remove

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