A New Approach to Generate Frequent Itemsets in Mining Image Association Rules

DU Lin; CHEN Yun-liang; ZHU Jing

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A New Approach to Generate Frequent Itemsets in Mining Image Association Rules

更新时间：2026-09-04

- A New Approach to Generate Frequent Itemsets in Mining Image Association Rules
- Vol. 28, Issue 7, Pages: 121-124(2011)
- 作者机构：
  
  1. 中国地质大学计算机学院,湖北,武汉,430074
  2. 华中科技大学计算机学院武汉光电国家实验室,湖北,武汉,430074
- 作者简介：
- 基金信息：
- DOI：
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- Published：2011
- 稿件说明：
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杜琳, 陈云亮, 朱静. 一种新的在图像关联规则挖掘中产生频繁项集的方法[J]. 微电子学与计算机, 2011, 28(7): 121-124.

DU Lin, CHEN Yun-liang, ZHU Jing. A New Approach to Generate Frequent Itemsets in Mining Image Association Rules[J]. 2011, 28(7): 121-124.
杜琳, 陈云亮, 朱静. 一种新的在图像关联规则挖掘中产生频繁项集的方法[J]. 微电子学与计算机, 2011, 28(7): 121-124. DOI：

DU Lin, CHEN Yun-liang, ZHU Jing. A New Approach to Generate Frequent Itemsets in Mining Image Association Rules[J]. 2011, 28(7): 121-124. DOI：

摘要

提出了一种进行图像关联规则提取时产生频繁项集的方法——频繁项树.为便于频繁项树的运用

使用了bSQ的图像数据格式来重新组织图像数据

并在此基础上提出了频繁项树的截断、半深度优先、图像掩模和多层次灰度范围自动生成等优化技术

降低了算法的时间和空间复杂度

使其具有较高的运行效率和实用价值.

Abstract

This paper proposes an approach to generate frequent itemsets in mining image association rules——Frequent Item Tree.We utilize bSQ image format to re-organize the image data to apply frequent item tree.Moreover

this paper propose several optimization techniques

including frequent item tree pruning

semi-depth-first search

image mask

and multi-level gray generation

to decrease the time and space complexity.

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Related Author

ZHANG Jin-hua

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Related Institution

School of Computer Science and Technology, Zhoukou Normal University

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