The automatic creation of a repository of the building’s floor plan helps a lot to the architects to reuse them. The basic approach is to extract and recognize texts, symbols or graphics to retrieve the information of the floor plan from the images. This paper proposes a floor plan information retrieval algorithm. The proposed algorithm is based on shape extraction and room identification.\(\alpha \)-shape is used for finding an accurate shape. From the detected shapes, actual areas of rooms are calculated. Later, a regression model-based binary room classification model is proposed to classify them into room-type, i.e., bedroom, drawing room, kitchen, and non-room-type, i.e., parking porch, bathroom, study room and prayer room. The proposed model is tested on the CVC-FP dataset with an average room detection accuracy of 85.71% and room recognition accuracy of 88%.

自动创建建筑物平面图存储库对建筑师重用它们有很大帮助。基本方法是提取和识别文本，符号或图形，以从图像中检索平面图的信息。本文提出了一种平面图信息检索算法。该算法基于形状提取和房间识别。\（\α \）-shape用于查找准确的形状。根据检测到的形状，计算房间的实际面积。随后，提出了一种基于回归模型的二元房间分类模型，将其分为房间类型，即卧室，客厅，厨房和非房间类型，即门廊，浴室，书房和祈祷室。该模型在CVC-FP数据集上进行了测试，平均房间检测准确度为85.71％，房间识别准确度为88％。