摘要:在我們的日的常生活中可以在很多地方看到圖像，而圖像是我們生活中得到信息的一種最基本的來(lái)源。我們有必要更好的發(fā)展與研究圖像處理這一課題。而用于圖像處理的方法現(xiàn)在也是多種多樣的，目前人工智能算法在處理圖像問(wèn)題上得到了越來(lái)越多的應(yīng)用。

　　　本課題研究的是人工智能算法在圖像分割中的應(yīng)用。人工智能是近些年來(lái)興起一門(mén)學(xué)科，在各個(gè)行業(yè)、領(lǐng)域都有著十分重要的作用。比如：在智能機(jī)器、智能控制、人工生命、圖像處理與模式識(shí)別中都有著一定的作用。人工智能算法也是多種多樣的，包含了許多不同的算法。其中包括了：遺傳算法、神經(jīng)網(wǎng)絡(luò)、人工免疫系統(tǒng)、小波變換、蟻群算法、粒子群算法等。而遺傳算法又是人工智能中比較重要的一門(mén)算法。它是一種迭代式的智能優(yōu)化算法，遺傳算法它還具有魯棒性、并行性、自適應(yīng)性，還有其收斂速度快的特點(diǎn)。遺傳算法在圖像分割中通常是幫助確定分割圖像的閾值。

　　　本文內(nèi)容包括了遺傳算法，還有它的生物學(xué)基礎(chǔ)、發(fā)展歷史、基本原理、特點(diǎn)以及基本操作流程。其次本文介紹了圖像分割中的一下典型算法。例如：基于閾值分割的圖像分割方法；基于邊緣檢測(cè)的圖像分割方法；基于區(qū)域的圖像分割方法。還簡(jiǎn)單介紹了幾種人工智能算法，最后講解了遺傳算法在圖像分割以及一些醫(yī)學(xué)圖片中的一些簡(jiǎn)單的應(yīng)用。在腎臟切片細(xì)胞中的腎小球細(xì)胞的檢測(cè)，我們需要將腎小球細(xì)胞提取出來(lái)以便進(jìn)行更好的分析與研究。其中，主要對(duì)如何將腎小球細(xì)胞通過(guò)怎么樣的步驟、方法。

關(guān)鍵詞：遺傳算法 人工智能 腎小球細(xì)胞 閾值分割 圖像分割

ABSTRACT:Often in our daily life can be seen in many places in the image, the image is in our life is one of the most basic source of information. It is necessary for us to better development and the research of image processing this issue. And is used for image processing method is now also is varied, the artificial intelligence algorithm in image processing is applied more and more on the issue. This topic is the study of the application of artificial intelligence algorithm in image segmentation. Artificial intelligence is a subject about the rise in recent years, in the field of various industries, has a very important role. Such as: the intelligent machine, intelligent control, artificial life, image processing and pattern recognition has a certain effect.

　　　Is also a variety of artificial intelligence algorithm, which contains many different algorithms .Artificial intelligence algorithms include: Genetic Algorithm (GA)、Neural Network、Artificial Immune System、Wavelet Transform 、Ant Colony Algorithm, Particle Swarm Optimization (PSO) Algorithm. Among them it is a kind of iterative genetic algorithm of intelligent optimization algorithm, genetic algorithm (GA) which has robustness, parallelism, adaptability, and the characteristic of its convergence speed is fast. Genetic algorithms in image segmentation are often help to determine the threshold of image segmentation. This article will focus on introduce some knowledge and application of genetic algorithm. The article content includes the genetic algorithm, and its biological basis, development history, basic principle, characteristics and basic operation process. Secondly, this paper introduces some typical algorithms in image segmentation. For example, the image segmentation method based on threshold segmentation; the image segmentation method based on edge detection; Image segmentation method based on region. Also introduced several artificial intelligence algorithms. After introduces the genetic algorithm in image segmentation, and some simple applications in some medical images. In kidney cells in the kidney biopsy cell detection, we need to pick up the kidney cells in order to better analysis and research. Among them, mainly on how to kidney cell through how the steps and methods.

Keywords: Genetic Algorithm (GA)   Artificial Intelligence   kidney Cells Image

Segmentation   Threshold Segmentation