In the era of the big data analysis, genomic signal processing (GSP) is gaining popularity to analyze the genomics data. GSP is used to extract the useful or hidden information from the genomics data such as DNA sequences using digital signal processing tools. The hidden information is closely associated with the different biological functionalities in the living organisms. CpG Island is one of such hidden information in DNA sequences, which is associated with the gene silencing, cancers and many other epigenetic diseases. Therefore, the extraction of the information about the CpG islands is highly needed to serve the people. So, in this work an algorithm based on wavelet transform has been proposed to overcome the fixed window length limitation of short-time Fourier transform based method for the detection of CpG Islands. The performance assessment of proposed method has been carried out on hundred DNA sequences of human species and detection performance has been improved over other state of art methods in terms of sensitivity, accuracy, and F-measure.