Content-based image retrieval (CBIR) is an active research field in the domain of information retrieval. This domain is widely studied in the last two decades and there are lots of approaches are introduced to handle this. Most of the existing CBIR schemes consider shape, color, or texture features of the objects in the image to find similar images for the retrieval purpose. In this manuscript, we introduce a CBIR scheme to retrieve the relevant images based on the textual information present in the images rather than other features. The proposed scheme will take an image as the input and retrieve the images which contain the common text information. From both the query image and from all the images in the image pool, the proposed scheme will identify the text by using the text detection approach. It might be noted that the text detection from natural image scenes is not always working perfectly. So to do the matching between the query image and the images in the image pool, we have used the length of the longest common sub-sequences as the criteria. The experimental study of the proposed scheme is carried and the results show that the proposed scheme works well.