基于互補(bǔ)空間信息的多目標(biāo)進(jìn)化聚類圖像分割
doi: 10.11999/JEIT140371 cstr: 32379.14.JEIT140371
基金項(xiàng)目:
國家自然科學(xué)基金(61102095, 61202153, 61340040)，陜西省科技計(jì)劃(2014KJXX-72)和陜西省自然科學(xué)基礎(chǔ)研究計(jì)劃(2012JQ8045, 2014JQ8336, 2014JM8307, 2013JM3081) 資助課題
Multi-objective Evolutionary Clustering with Complementary Spatial Information for Image Segmentation
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摘要: 現(xiàn)有的多目標(biāo)進(jìn)化聚類算法應(yīng)用于圖像分割時(shí)，沒有考慮圖像的任何空間信息，使得該類算法在含噪圖像上的分割性能不理想。該文鑒于圖像的局部空間信息和非局部空間信息的互補(bǔ)性，試圖將這兩種空間信息同時(shí)引入到聚類有效性函數(shù)中，構(gòu)造了融合互補(bǔ)空間信息的目標(biāo)函數(shù)，進(jìn)而提出了應(yīng)用于圖像分割的基于互補(bǔ)空間信息的多目標(biāo)進(jìn)化聚類算法。該算法采用染色體可變長(zhǎng)編碼策略在進(jìn)化過程中自動(dòng)確定圖像分割數(shù)目，減少了人為干預(yù)。自然圖像的分割實(shí)驗(yàn)表明，該算法不但能在含噪圖像上取得較為滿意的分割性能，而且適用于多種類型的含噪圖像。
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關(guān)鍵詞:
- 圖像分割 /
- 多目標(biāo)進(jìn)化聚類 /
- 互補(bǔ)空間信息 /
- 局部空間信息
Abstract: When existing multi-objective evolutionary clustering algorithms is applied to image segmentation, it can not obtain satisfactory segmentation performance on an image corrupted by noise due to no consideration of any spatial information derived from the image. Based on the complementarity of the local spatial information and the non local spatial information of the image, these two kinds of spatial information are introduced into a cluster validity function, and a novel objective function with complementary spatial information is constructed, and then a multi-objective evolutionary clustering algorithm with complementary spatial information for image segmentation is proposed. In order to reduce human intervention, the variable string length real coded technique is adopted to determine automatically the number of clusters during the evolving process. Natural image segmentation experiments show that the proposed method not only can obtain satisfactory segmentation performance on noisy images, but also can be suitable for many types of noisy images. -
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