关键词: 深度学习, 卷积神经网络, 目标检测, 倾斜文本定位, 聚类

Abstract:

In order to improve the accuracy of tilted text region location, a YOLO_BOX location model based on improved YOLO algorithm is proposed. Anchors of different sizes are set to train the images, and LOSS function is defined to train the prediction model. K-means algorithm is adopted to cluster the boxes, and NMS method is applied to filter the redundant candidate boxes. Angle Correct algorithm is used to gray the clustered box, and the variance of the gray value of the pixels is calculated to get the tilt angle of the text and correct the angle. Experimental results show that the optimized YOLO_BOX localization model has high accuracy and recall rate for the inclined text area location in the natural scene on ICDAR2015 data set.

Key words: deep learning, Convolutional Neural Network（CNN）, object detection, tilt text region location, clustering