Research of segmentation method on color image of Lingwu long jujubes based on the maximum entropy

Abstract

Abstract This paper researches on methods of the color image segmentation method of Lingwu long jujubes based on the maximum entropy to achieve the accuracy of image segmentation and improve accuracy of machine recognition. According to law between the color of Lingwu long jujubes and characteristic of environment, starting from the hue information, this paper is first to explore the difference between the hue of Lingwu long jujubes and the environment which it lives and then use maximum entropy to segment image. It finds optimal threshold by mathematical criterion judging the accuracy of image segmentation. The method of pre-processing of image is mean filter firstly. Then, it extracts hue information of true color image and uses maximum entropy for image segmentation, judging accuracy of image segmentation by segmentation area whether it is in accordance with the 3σ principle. Mathematical morphology is used for smoothing image and eliminating small holes. Finally, segmented image will be obtained through labeling the image by using methods of labeled image and using characteristic parameters for extracting feature. By comparing the segmentation effect with artificial method of the 30 Lingwu long jujubes images, it proves that the color image segmentation method of Lingwu long jujubes based on the maximum entropy has good effect to extract the object region. The accuracy of segmentation rate is up to 89.60%. The time that the algorithm run is 1.3132 s.

Keywords

• Maximum entropy
• Image processing
• Image segmentation
• Adaptive threshold
• Lingwu long jujubes