Recent studies on remote detection methods were mostly for improving variables like sensing distance, sensitivity and power consumption. Especially using anisotropic magneto-resistive sensors with low power consumption and high sensitivity for detecting subsurface magnetic materials became very popular in last decades. In our study, for detecting subsurface materials, we have used fluxgate sensor network for having even higher sensitivity and also minimizing the power consumption by detecting the changing rates of horizontal component of earth's magnetic flux which is assumed to be very low. We have constituted a magnetic measurement system which comprises a detector system, which has a mechanism enables sensors to move in 3-D space, a data acquisition module for processing and sending all sensor information, and a computer for running the magnetic flux data evaluation and recording software. Using this system, tests are carried out to detect anomalies on horizontal component of earth's magnetic flux which is created by different subsurface materials with known magnetic, chemical and geometric properties. The harmonics of horizontal component of earth's magnetic flux in scanned area are analyzed by the help of DSP Lock-In amplifier and the amplitudes of high variation harmonics are shown as computer graphics. Using the graphic information, the upside surface geometry of subsurface material is defined. For identifying the magnetic anomalies, we have used the scale-invariant feature transform (SIFT)-binary robust invariant scalable keypoints (BRISKs) as keypoint and descriptor. We used an algorithm for matching the newly scanned image to the closest image in database which is constituted of mines and possible other metal objects like cans, etc. Results show that, if the proposed detection system is used instead of metal detectors which cannot distinguish mines from other metal materials and alert for every type of metal with different geometries, it can be said that miss alarm count, work force and time can be decreased dramatically. In this paper, mostly the setup of the system is described and in Appendix A some experimental outputs of the system for different geometries of metal samples are given. And also for comparing the results of the proposed system, additional experiments are carried out with a different type of sensor chip, namely KMZ51, and also given in Appendix A. (C) 2015 Elsevier Ltd. All rights reserved.