In this paper, a Modular Fractional Chaotic Sine Map (MFC-SM) has been introduced to achieve high Lyapunov exponent values and completely chaotic behavior of the bifurcation diagram for high level security. The proposed MFC-SM is compared with the conventional non MFC-SM and it has an excellent chaotic analysis. In addition, the randomness test results indicate that the proposed MFC-SM shows better performance and satisfy all randomness tests. Due to the excellent chaotic properties and good randomization results for the proposed MFC-SM, it is used to be cooperated with the biometric digital identity to achieve dynamic chaotic biometric digital identity. Also, for real time image encryption, both Discrete Wavelet Transform (DWT) partial image encryption and Isomorphic Elliptic Curve (IEC) key exchange are used. In addition, the biometric digital identity is extracted from the user fingerprint image as fingerprint minutia data incorporated with the proposed MFC-SM and hence, a new Dynamic Fractional Chaotic Biometric Digital Identity IEC (DFC-BID-IEC) has been introduced. Dynamic Fractional Chaotic Key Generator (DFC-KG) is used to control the key schedule for all encryption and decryption processing. The encryption process consists of the confusion and diffusion steps. In the confusion step, the 2D Arnold Cat Map (ACM) is used with secret parameters taken from DFC-KG. Also, the diffusion step is based on the dynamic chaotic self-invertible secret key matrix which can be generated from the proposed MFC-SM. The IEC key exchange secret parameters are generated based on Elliptic Curve Diffie-Hellman (ECDH) key exchange and the isomorphism parametre. Statistical analysis, differential analysis and key sensitivity tests are performed to estimate the security strengths of the proposed DFC-BID-IEC system. The experimental results show that the proposed algorithm is robust against common signal processing attacks and provides a high security level and high speed for image encryption application.