Particle swarm optimization ITTI model-based white cell region extraction method

Abstract

The invention discloses a particle swarm optimization ITTI model-based white cell region extraction method and belongs to the image processing technical field. According to the method, firstly, direction, brightness and color saliency features of an original grayscale map are extracted through using Gaussian filtering and multiscale normalization; secondly, adaptive coefficient fusion is performed on the three kinds of saliency features based on a principle that the contributions of eyes to visual characteristics are inconsistent, so that a saliency map can be obtained; and finally, region of interest extraction is performed on the saliency map through using an improved particle swarm optimization algorithm-based Otsu method, so that a complete white cell region can be obtained. As indicated by experiments, the method of the invention can better extract a complete white cell region compared with other methods for extracting regions of interest of a bone marrow cell image.

Description

technical field [0001] The invention relates to the technical field of image processing, more specifically, to a method for extracting white blood cell regions based on particle swarm optimization ITTI model. Background technique [0002] As the "guard of the human body", white blood cells play an important role in the fight against diseases. The abnormalities in the number and morphology of different types of white blood cells are of high value in the diagnosis of diseases. In practical application, pathological inspectors find lesions mainly by looking for abnormal parts in microcytograms, and manual operation inevitably produces heavy workload and fatigue, which leads to problems such as missed judgments and wrong judgments. If the computer is used to automatically extract the white blood cells of interest to the human eye in the cell image, the work efficiency of the human eye to identify abnormal white blood cells can be significantly improved, and it has practical appl...

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Problems solved by technology

[0006] According to the principle that the contribution of human eyes to different salient features is inconsistent, the present invention changes the way of combining salient features in the traditional ITTI visual model; and aims at the problems of inaccurate threshold value and long running time generated by Otsu extracting the region of interest of the salient map, The Otsu algorithm based on the particle swarm optimization algorithm is introduced, and a white blood cell area extraction method based on the particle swarm optimization ITTI model is provided. The present invention first uses the Gaussian pyramid to decompose the direction, brightness, and color feature components, and then through the central peripheral operator and The multi-scale normalization operation obtains the saliency feature map of the three components, and then uses the improved adaptive coefficient fusion method to obtain the saliency map, and finally uses the Otsu method based on the improved particle swarm optimization algorithm to perform the region of interest on the saliency map Extraction, the present invention can effectively extract the white blood cell area in the bone marrow cell image

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